Learning curves for urological procedures: a systematic review.

PubMed

Abboudi, Hamid; Khan, Mohammed Shamim; Guru, Khurshid A; Froghi, Saied; de Win, Gunter; Van Poppel, Hendrik; Dasgupta, Prokar; Ahmed, Kamran

2014-10-01

To determine the number of cases a urological surgeon must complete to achieve proficiency for various urological procedures. The MEDLINE, EMBASE and PsycINFO databases were systematically searched for studies published up to December 2011. Studies pertaining to learning curves of urological procedures were included. Two reviewers independently identified potentially relevant articles. Procedure name, statistical analysis, procedure setting, number of participants, outcomes and learning curves were analysed. Forty-four studies described the learning curve for different urological procedures. The learning curve for open radical prostatectomy ranged from 250 to 1000 cases and for laparoscopic radical prostatectomy from 200 to 750 cases. The learning curve for robot-assisted laparoscopic prostatectomy (RALP) has been reported to be 40 procedures as a minimum number. Robot-assisted radical cystectomy has a documented learning curve of 16-30 cases, depending on which outcome variable is measured. Irrespective of previous laparoscopic experience, there is a significant reduction in operating time (P = 0.008), estimated blood loss (P = 0.008) and complication rates (P = 0.042) after 100 RALPs. The available literature can act as a guide to the learning curves of trainee urologists. Although the learning curve may vary among individual surgeons, a consensus should exist for the minimum number of cases to achieve proficiency. The complexities associated with defining procedural competence are vast. The majority of learning curve trials have focused on the latest surgical techniques and there is a paucity of data pertaining to basic urological procedures. © 2013 The Authors. BJU International © 2013 BJU International.

On the necessity of U-shaped learning.

PubMed

Carlucci, Lorenzo; Case, John

2013-01-01

A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning English past tense) has become a central topic in the Cognitive Science debate about learning models. Antagonist models (e.g., connectionism versus nativism) are often judged on their ability of modeling or accounting for U-shaped behavior. The prior literature is mostly occupied with explaining how U-shaped behavior occurs. Instead, we are interested in the necessity of this kind of apparently inefficient strategy. We present and discuss a body of results in the abstract mathematical setting of (extensions of) Gold-style computational learning theory addressing a mathematically precise version of the following question: Are there learning tasks that require U-shaped behavior? All notions considered are learning in the limit from positive data. We present results about the necessity of U-shaped learning in classical models of learning as well as in models with bounds on the memory of the learner. The pattern emerges that, for parameterized, cognitively relevant learning criteria, beyond very few initial parameter values, U-shapes are necessary for full learning power! We discuss the possible relevance of the above results for the Cognitive Science debate about learning models as well as directions for future research. Copyright © 2013 Cognitive Science Society, Inc.

Implementation Learning and Forgetting Curve to Scheduling in Garment Industry

NASA Astrophysics Data System (ADS)

Muhamad Badri, Huda; Deros, Baba Md; Syahri, M.; Saleh, Chairul; Fitria, Aninda

2016-02-01

The learning curve shows the relationship between time and the cumulative number of units produced which using the mathematical description on the performance of workers in performing repetitive works. The problems of this study is level differences in the labors performance before and after the break which affects the company's production scheduling. The study was conducted in the garment industry, which the aims is to predict the company production scheduling using the learning curve and forgetting curve. By implementing the learning curve and forgetting curve, this paper contributes in improving the labors performance that is in line with the increase in maximum output 3 hours productive before the break are 15 unit product with learning curve percentage in the company is 93.24%. Meanwhile, the forgetting curve improving maximum output 3 hours productive after the break are 11 unit product with the percentage of forgetting curve in the company is 92.96%. Then, the obtained 26 units product on the productive hours one working day is used as the basic for production scheduling.

A theory for how sensorimotor skills are learned and retained in noisy and nonstationary neural circuits

PubMed Central

Ajemian, Robert; D’Ausilio, Alessandro; Moorman, Helene; Bizzi, Emilio

2013-01-01

During the process of skill learning, synaptic connections in our brains are modified to form motor memories of learned sensorimotor acts. The more plastic the adult brain is, the easier it is to learn new skills or adapt to neurological injury. However, if the brain is too plastic and the pattern of synaptic connectivity is constantly changing, new memories will overwrite old memories, and learning becomes unstable. This trade-off is known as the stability–plasticity dilemma. Here a theory of sensorimotor learning and memory is developed whereby synaptic strengths are perpetually fluctuating without causing instability in motor memory recall, as long as the underlying neural networks are sufficiently noisy and massively redundant. The theory implies two distinct stages of learning—preasymptotic and postasymptotic—because once the error drops to a level comparable to that of the noise-induced error, further error reduction requires altered network dynamics. A key behavioral prediction derived from this analysis is tested in a visuomotor adaptation experiment, and the resultant learning curves are modeled with a nonstationary neural network. Next, the theory is used to model two-photon microscopy data that show, in animals, high rates of dendritic spine turnover, even in the absence of overt behavioral learning. Finally, the theory predicts enhanced task selectivity in the responses of individual motor cortical neurons as the level of task expertise increases. From these considerations, a unique interpretation of sensorimotor memory is proposed—memories are defined not by fixed patterns of synaptic weights but, rather, by nonstationary synaptic patterns that fluctuate coherently. PMID:24324147

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia

PubMed Central

Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Purpose Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Methods Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. Results We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Conclusion Learning curve seems to complete after performing 16 cases. PMID:28686640

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia.

PubMed

Yano, Fumiaki; Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Learning curve seems to complete after performing 16 cases.

Systematic review of learning curves for minimally invasive abdominal surgery: a review of the methodology of data collection, depiction of outcomes, and statistical analysis.

PubMed

Harrysson, Iliana J; Cook, Jonathan; Sirimanna, Pramudith; Feldman, Liane S; Darzi, Ara; Aggarwal, Rajesh

2014-07-01

To determine how minimally invasive surgical learning curves are assessed and define an ideal framework for this assessment. Learning curves have implications for training and adoption of new procedures and devices. In 2000, a review of the learning curve literature was done by Ramsay et al and it called for improved reporting and statistical evaluation of learning curves. Since then, a body of literature is emerging on learning curves but the presentation and analysis vary. A systematic search was performed of MEDLINE, EMBASE, ISI Web of Science, ERIC, and the Cochrane Library from 1985 to August 2012. The inclusion criteria are minimally invasive abdominal surgery formally analyzing the learning curve and English language. 592 (11.1%) of the identified studies met the selection criteria. Time is the most commonly used proxy for the learning curve (508, 86%). Intraoperative outcomes were used in 316 (53%) of the articles, postoperative outcomes in 306 (52%), technical skills in 102 (17%), and patient-oriented outcomes in 38 (6%) articles. Over time, there was evidence of an increase in the relative amount of laparoscopic and robotic studies (P < 0.001) without statistical evidence of a change in the complexity of analysis (P = 0.121). Assessment of learning curves is needed to inform surgical training and evaluate new clinical procedures. An ideal analysis would account for the degree of complexity of individual cases and the inherent differences between surgeons. There is no single proxy that best represents the success of surgery, and hence multiple outcomes should be collected.

Assessment of Postflight Locomotor Performance Utilizing a Test of Functional Mobility: Strategic and Adaptive Responses

NASA Technical Reports Server (NTRS)

Warren, L. E.; Mulavara, A. P.; Peters, B. T.; Cohen, H. S.; Richards, J. T.; Miller, C. A.; Brady, R.; Ruttley, T. M.; Bloomberg, J. J.

2006-01-01

Space flight induces adaptive modification in sensorimotor function, allowing crewmembers to operate in the unique microgravity environment. This adaptive state, however, is inappropriate for a terrestrial environment. During a re-adaptation period upon their return to Earth, crewmembers experience alterations in sensorimotor function, causing various disturbances in perception, spatial orientation, posture, gait, and eye-head coordination. Following long duration space flight, sensorimotor dysfunction would prevent or extend the time required to make an emergency egress from the vehicle; compromising crew safety and mission objectives. We are investigating two types of motor learning that may interact with each other and influence a crewmember's ability to re-adapt to Earth's gravity environment. In strategic learning, crewmembers make rapid modifications in their motor control strategy emphasizing error reduction. This type of learning may be critical during the first minutes and hours after landing. In adaptive learning, long-term plastic transformations occur, involving morphological changes and synaptic modification. In recent literature these two behavioral components have been associated with separate brain structures that control the execution of motor strategies: the strategic component was linked to the posterior parietal cortex and the adaptive component was linked to the cerebellum (Pisella, et al. 2004). The goal of this paper was to demonstrate the relative contributions of the strategic and adaptive components to the re-adaptation process in locomotor control after long duration space flight missions on the International Space Station (ISS). The Functional Mobility Test (FMT) was developed to assess crewmember s ability to ambulate postflight from an operational and functional perspective. Sixteen crewmembers were tested preflight (3 sessions) and postflight (days 1, 2, 4, 7, 25) following a long duration space flight (approx 6 months) on the ISS. We have further analyzed the FMT data to characterize strategic and adaptive components during the postflight readaptation period. Crewmembers walked at a preferred pace through an obstacle course set up on a base of 10 cm thick medium density foam (Sunmate Foam, Dynamic Systems, Inc., Leicester, NC). The 6.0m X 4.0m course consisted of several pylons made of foam; a Styrofoam barrier 46.0cm high that crewmembers stepped over; and a portal constructed of two Styrofoam blocks, each 31cm high, with a horizontal bar covered by foam and suspended from the ceiling which was adjusted to the height of the crewmember s shoulder. The portal required crewmembers to bend at the waist and step over a barrier simultaneously. All obstacles were lightweight, soft and easily knocked over. Crewmembers were instructed to walk through the course as quickly and as safely as possible without touching any of the objects on the course. This task was performed three times in the clockwise direction and three times in the counterclockwise direction that was randomly chosen. The dependent measures for each trial were: time to complete the course (seconds) and the number of obstacles touched or knocked down. For each crewmember, the time to complete each FMT trial from postflight days 1, 2, 4, 7 and 25 were further analyzed. A single logarithmic curve using a least squares calculation was fit through these data to produce a single comprehensive curve (macro). This macro curve composed of data spanning 25 days, illustrates the re-adaptive learning function over the longer time scale term. Additionally, logarithmic curves were fit to the 6 data trials within each individual post flight test day to produce 5 separate daily curves. These micro curves, produced from data obtained over the course of minutes, illustrates the strategic learning function exhibited over a relative shorter time scale. The macro curve for all subjects exhibited adaptive motor learning patterns over the 25 day period. Howev, 9/16 crewmembers exhibited significant strategic motor learning patterns in their micro curves, as defined by m > 1 in the equation of the line y=m*LN(x) +b. These data indicate that postflight recovery in locomotor function involves both strategic and adaptive mechanisms. Future countermeasures will be designed to enhance both recovery processes.

Learning curves in health care.

PubMed

Waldman, J Deane; Yourstone, Steven A; Smith, Howard L

2003-01-01

This article explores the uses of learning curve theory in medicine. Though effective application of learning curve theory in health care can result in higher quality and lower cost, it is seldom methodically applied in clinical practice. Fundamental changes are necessary in the corporate culture of medicine in order to capitalize maximally on the benefits of learning.

Manufacturing complexity analysis

NASA Technical Reports Server (NTRS)

Delionback, L. M.

1977-01-01

The analysis of the complexity of a typical system is presented. Starting with the subsystems of an example system, the step-by-step procedure for analysis of the complexity of an overall system is given. The learning curves for the various subsystems are determined as well as the concurrent numbers of relevant design parameters. Then trend curves are plotted for the learning curve slopes versus the various design-oriented parameters, e.g. number of parts versus slope of learning curve, or number of fasteners versus slope of learning curve, etc. Representative cuts are taken from each trend curve, and a figure-of-merit analysis is made for each of the subsystems. Based on these values, a characteristic curve is plotted which is indicative of the complexity of the particular subsystem. Each such characteristic curve is based on a universe of trend curve data taken from data points observed for the subsystem in question. Thus, a characteristic curve is developed for each of the subsystems in the overall system.

Taking the brakes off the learning curve.

PubMed

Gheysen, Freja; Lasne, Gabriel; Pélégrini-Issac, Mélanie; Albouy, Genevieve; Meunier, Sabine; Benali, Habib; Doyon, Julien; Popa, Traian

2017-03-01

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Renal mass anatomic characteristics and perioperative outcomes of laparoscopic partial nephrectomy: a critical analysis.

PubMed

Tsivian, Matvey; Ulusoy, Said; Abern, Michael; Wandel, Ayelet; Sidi, A Ami; Tsivian, Alexander

2012-10-01

Anatomic parameters determining renal mass complexity have been used in a number of proposed scoring systems despite lack of a critical analysis of their independent contributions. We sought to assess the independent contribution of anatomic parameters on perioperative outcomes of laparoscopic partial nephrectomy (LPN). Preoperative imaging studies were reviewed for 147 consecutive patients undergoing LPN for a single renal mass. Renal mass anatomy was recorded: Size, growth pattern (endo-/meso-/exophytic), centrality (central/hilar/peripheral), anterior/posterior, lateral/medial, polar location. Multivariable models were used to determine associations of anatomic parameters with warm ischemia time (WIT), operative time (OT), estimated blood loss (EBL), intra- and postoperative complications, as well as renal function. All models were adjusted for the learning curve and relevant confounders. Median (range) tumor size was 3.3 cm (1.5-11 cm); 52% were central and 14% hilar. While 44% were exophytic, 23% and 33% were mesophytic and endophytic, respectively. Anatomic parameters did not uniformly predict perioperative outcomes. WIT was associated with tumor size (P=0.068), centrality (central, P=0.016; hilar, P=0.073), and endophytic growth pattern (P=0.017). OT was only associated with tumor size (P<0.001). No anatomic parameter predicted EBL. Tumor centrality increased the odds of overall and intraoperative complications, without reaching statistical significance. Postoperative renal function was not associated with any of the anatomic parameters considered after adjustment for baseline function and WIT. Learning curve, considered as a confounder, was independently associated with reduced WIT and OT as well as reduced odds of intraoperative complications. This study provides a detailed analysis of the independent impact of renal mass anatomic parameters on perioperative outcomes. Our findings suggest diverse independent contributions of the anatomic parameters to the different measures of outcomes (WIT, OT, EBL, complications, and renal function) emphasizing the importance of the learning curve.

Unsupervised classification of variable stars

NASA Astrophysics Data System (ADS)

Valenzuela, Lucas; Pichara, Karim

2018-03-01

During the past 10 years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric data sets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data come from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query-based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire data set of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

A Cognitive Machine Learning Algorithm for Cardiac Imaging: A Pilot Study for Differentiating Constrictive Pericarditis from Restrictive Cardiomyopathy

PubMed Central

Sengupta, Partho P.; Huang, Yen-Min; Bansal, Manish; Ashrafi, Ali; Fisher, Matt; Shameer, Khader; Gall, Walt; Dudley, Joel T

2016-01-01

Background Associating a patient’s profile with the memories of prototypical patients built through previous repeat clinical experience is a key process in clinical judgment. We hypothesized that a similar process using a cognitive computing tool would be well suited for learning and recalling multidimensional attributes of speckle tracking echocardiography (STE) data sets derived from patients with known constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods and Results Clinical and echocardiographic data of 50 patients with CP and 44 with RCM were used for developing an associative memory classifier (AMC) based machine learning algorithm. The STE data was normalized in reference to 47 controls with no structural heart disease, and the diagnostic area under the receiver operating characteristic curve (AUC) of the AMC was evaluated for differentiating CP from RCM. Using only STE variables, AMC achieved a diagnostic AUC of 89·2%, which improved to 96·2% with addition of 4 echocardiographic variables. In comparison, the AUC of early diastolic mitral annular velocity and left ventricular longitudinal strain were 82.1% and 63·7%, respectively. Furthermore, AMC demonstrated greater accuracy and shorter learning curves than other machine learning approaches with accuracy asymptotically approaching 90% after a training fraction of 0·3 and remaining flat at higher training fractions. Conclusions This study demonstrates feasibility of a cognitive machine learning approach for learning and recalling patterns observed during echocardiographic evaluations. Incorporation of machine learning algorithms in cardiac imaging may aid standardized assessments and support the quality of interpretations, particularly for novice readers with limited experience. PMID:27266599

Transitive inference in adults with autism spectrum disorders

PubMed Central

Solomon, Marjorie; Frank, Michael J.; Smith, Anne C.; Ly, Stanford; Carter, Cameron S.

2012-01-01

Individuals with autism spectrum disorders (ASDs) exhibit intact rote learning with impaired generalization. A transitive inference paradigm, involving training on four sequentially presented stimulus pairs containing overlapping items, with subsequent testing on two novel pairs, was used to investigate this pattern of learning in 27 young adults with ASDs and 31 matched neurotypical individuals (TYPs). On the basis of findings about memory and neuropathology, we hypothesized that individuals with ASDs would use a relational flexibility/conjunctive strategy reliant on an intact hippocampus, versus an associative strength/value transfer strategy requiring intact interactions between the prefrontal cortex and the striatum. Hypotheses were largely confirmed. ASDs demonstrated reduced interference from intervening pairs in early training; only TYPs formed a serial position curve by test; and ASDs exhibited impairments on the novel test pair consisting of end items with intact performance on the inner test pair. However, comparable serial position curves formed for both groups by the end of the first block. PMID:21656344

Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models

ERIC Educational Resources Information Center

Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R.

2009-01-01

This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…

da Vinci skills simulator for assessing learning curve and criterion-based training of robotic basic skills.

PubMed

Brinkman, Willem M; Luursema, Jan-Maarten; Kengen, Bas; Schout, Barbara M A; Witjes, J Alfred; Bekkers, Ruud L

2013-03-01

To answer 2 research questions: what are the learning curve patterns of novices on the da Vinci skills simulator parameters and what parameters are appropriate for criterion-based robotic training. A total of 17 novices completed 2 simulator sessions within 3 days. Each training session consisted of a warming-up exercise, followed by 5 repetitions of the "ring and rail II" task. Expert participants (n = 3) performed a warming-up exercise and 3 repetitions of the "ring and rail II" task on 1 day. We analyzed all 9 parameters of the simulator. Significant learning occurred on 5 parameters: overall score, time to complete, instrument collision, instruments out of view, and critical errors within 1-10 repetitions (P <.05). Economy of motion and excessive instrument force only showed improvement within the first 5 repetitions. No significant learning on the parameter drops and master workspace range was found. Using the expert overall performance score (n = 3) as a criterion (overall score 90%), 9 of 17 novice participants met the criterion within 10 repetitions. Most parameters showed that basic robotic skills are learned relatively quickly using the da Vinci skills simulator, but that 10 repetitions were not sufficient for most novices to reach an expert level. Some parameters seemed inappropriate for expert-based criterion training because either no learning occurred or the novice performance was equal to expert performance. Copyright © 2013 Elsevier Inc. All rights reserved.

Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities.

PubMed

Kepinska, Olga; Pereda, Ernesto; Caspers, Johanneke; Schiller, Niels O

2017-12-01

The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power. Copyright © 2017 Elsevier Inc. All rights reserved.

The learning curve of laparoscopic holecystectomy in general surgery resident training: old age of the patient may be a risk factor?

PubMed

Ferrarese, Alessia; Gentile, Valentina; Bindi, Marco; Rivelli, Matteo; Cumbo, Jacopo; Solej, Mario; Enrico, Stefano; Martino, Valter

2016-01-01

A well-designed learning curve is essential for the acquisition of laparoscopic skills: but, are there risk factors that can derail the surgical method? From a review of the current literature on the learning curve in laparoscopic surgery, we identified learning curve components in video laparoscopic cholecystectomy; we suggest a learning curve model that can be applied to assess the progress of general surgical residents as they learn and master the stages of video laparoscopic cholecystectomy regardless of type of patient. Electronic databases were interrogated to better define the terms "surgeon", "specialized surgeon", and "specialist surgeon"; we surveyed the literature on surgical residency programs outside Italy to identify learning curve components, influential factors, the importance of tutoring, and the role of reference centers in residency education in surgery. From the definition of acceptable error, self-efficacy, and error classification, we devised a learning curve model that may be applied to training surgical residents in video laparoscopic cholecystectomy. Based on the criteria culled from the literature, the three surgeon categories (general, specialized, and specialist) are distinguished by years of experience, case volume, and error rate; the patients were distinguished for years and characteristics. The training model was constructed as a series of key learning steps in video laparoscopic cholecystectomy. Potential errors were identified and the difficulty of each step was graded using operation-specific characteristics. On completion of each procedure, error checklist scores on procedure-specific performance are tallied to track the learning curve and obtain performance indices of measurement that chart the trainee's progress. The concept of the learning curve in general surgery is disputed. The use of learning steps may enable the resident surgical trainee to acquire video laparoscopic cholecystectomy skills proportional to the instructor's ability, the trainee's own skills, and the safety of the surgical environment. There were no patient characteristics that can derail the methods. With this training scheme, resident trainees may be provided the opportunity to develop their intrinsic capabilities without the loss of basic technical skills.

The learning curve of robot-assisted laparoscopic fundoplication in children: a prospective evaluation and CUSUM analysis.

PubMed

Cundy, Thomas P; Rowland, Simon P; Gattas, Nicholas E; White, Alan D; Najmaldin, Azad S

2015-06-01

Fundoplication is a leading application of robotic surgery in children, yet the learning curve for this procedure (RF) remains ill-defined. This study aims to identify various learning curve transition points, using cumulative summation (CUSUM) analysis. A prospective database was examined to identify RF cases undertaken during 2006-2014. Time-based surgical process outcomes were evaluated, as well as clinical outcomes. A total of 57 RF cases were included. Statistically significant transitions beyond the learning phase were observed at cases 42, 34 and 37 for docking, console and total operating room times, respectively. A steep early learning phase for docking time was overcome after 12 cases. There were three Clavien-Dindo grade ≥ 3 complications, with two patients requiring redo fundoplication. We identified numerous well-defined learning curve trends to affirm that experience confers significant temporal improvements. Our findings highlight the value of the CUSUM method for learning curve evaluation. Copyright © 2014 John Wiley & Sons, Ltd.

Is the learning curve endless? One surgeon's experience with robotic prostatectomy

NASA Astrophysics Data System (ADS)

Patel, Vipul; Thaly, Rahul; Shah, Ketul

2007-02-01

Introduction: After performing 1,000 robotic prostatectomies we reflected back on our experience to determine what defined the learning curve and the essential elements that were the keys to surmounting it. Method: We retrospectively assessed our experience to attempt to define the learning curve(s), key elements of the procedure, technical refinements and changes in technology that facilitated our progress. Result: The initial learning curve to achieve basic competence and the ability to smoothly perform the procedure in less than 4 hours with acceptable outcomes was approximately 25 cases. A second learning curve was present between 75-100 cases as we approached more complicated patients. At 200 cases we were comfortably able to complete the procedure routinely in less than 2.5 hours with no specific step of the procedure hindering our progression. At 500 cases we had the introduction of new instrumentation (4th arm, biopolar Maryland, monopolar scissors) that changed our approach to the bladder neck and neurovascular bundle dissection. The most challenging part of the procedure was the bladder neck dissection. Conclusion: There is no single parameter that can be used to assess or define the learning curve. We used a combination of factors to make our subjective definition this included: operative time, smoothness of technical progression during the case along with clinical outcomes. The further our case experience progressed the more we expected of our outcomes, thus we continually modified our technique and hence embarked upon yet a new learning curve.

An appraisal of the learning curve in robotic general surgery.

PubMed

Pernar, Luise I M; Robertson, Faith C; Tavakkoli, Ali; Sheu, Eric G; Brooks, David C; Smink, Douglas S

2017-11-01

Robotic-assisted surgery is used with increasing frequency in general surgery for a variety of applications. In spite of this increase in usage, the learning curve is not yet defined. This study reviews the literature on the learning curve in robotic general surgery to inform adopters of the technology. PubMed and EMBASE searches yielded 3690 abstracts published between July 1986 and March 2016. The abstracts were evaluated based on the following inclusion criteria: written in English, reporting original work, focus on general surgery operations, and with explicit statistical methods. Twenty-six full-length articles were included in final analysis. The articles described the learning curves in colorectal (9 articles, 35%), foregut/bariatric (8, 31%), biliary (5, 19%), and solid organ (4, 15%) surgery. Eighteen of 26 (69%) articles report single-surgeon experiences. Time was used as a measure of the learning curve in all studies (100%); outcomes were examined in 10 (38%). In 12 studies (46%), the authors identified three phases of the learning curve. Numbers of cases needed to achieve plateau performance were wide-ranging but overlapping for different kinds of operations: 19-128 cases for colorectal, 8-95 for foregut/bariatric, 20-48 for biliary, and 10-80 for solid organ surgery. Although robotic surgery is increasingly utilized in general surgery, the literature provides few guidelines on the learning curve for adoption. In this heterogeneous sample of reviewed articles, the number of cases needed to achieve plateau performance varies by case type and the learning curve may have multiple phases as surgeons add more complex cases to their case mix with growing experience. Time is the most common determinant for the learning curve. The literature lacks a uniform assessment of outcomes and complications, which would arguably reflect expertise in a more meaningful way than time to perform the operation alone.

Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance.

PubMed

Gaschler, Robert; Progscha, Johanna; Smallbone, Kieran; Ram, Nilam; Bilalić, Merim

2014-01-01

Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tournaments for at least 10 years. We analyze the performance development with the goal to test the adequacy of learning curves, and the skill acquisition theories they are based on, for describing and predicting expertise acquisition. On the one hand, we show that the skill acquisition theories implying a negative exponential learning curve do a better job in both describing early performance gains and predicting later trajectories of chess performance than those theories implying a power function learning curve. On the other hand, the learning curves of a large proportion of players show systematic qualitative deviations from the predictions of either type of skill acquisition theory. While skill acquisition theories predict larger performance gains in early years and smaller gains in later years, a substantial number of players begin to show substantial improvements with a delay of several years (and no improvement in the first years), deviations not fully accounted for by quantity of practice. The current work adds to the debate on how learning processes on a small time scale combine to large-scale changes.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

PubMed Central

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

The sales learning curve.

PubMed

Leslie, Mark; Holloway, Charles A

2006-01-01

When a company launches a new product into a new market, the temptation is to immediately ramp up sales force capacity to gain customers as quickly as possible. But hiring a full sales force too early just causes the firm to burn through cash and fail to meet revenue expectations. Before it can sell an innovative product efficiently, the entire organization needs to learn how customers will acquire and use it, a process the authors call the sales learning curve. The concept of a learning curve is well understood in manufacturing. Employees transfer knowledge and experience back and forth between the production line and purchasing, manufacturing, engineering, planning, and operations. The sales learning curve unfolds similarly through the give-and-take between the company--marketing, sales, product support, and product development--and its customers. As customers adopt the product, the firm modifies both the offering and the processes associated with making and selling it. Progress along the manufacturing curve is measured by tracking cost per unit: The more a firm learns about the manufacturing process, the more efficient it becomes, and the lower the unit cost goes. Progress along the sales learning curve is measured in an analogous way: The more a company learns about the sales process, the more efficient it becomes at selling, and the higher the sales yield. As the sales yield increases, the sales learning process unfolds in three distinct phases--initiation, transition, and execution. Each phase requires a different size--and kind--of sales force and represents a different stage in a company's production, marketing, and sales strategies. Adjusting those strategies as the firm progresses along the sales learning curve allows managers to plan resource allocation more accurately, set appropriate expectations, avoid disastrous cash shortfalls, and reduce both the time and money required to turn a profit.

Teaching Learning Curves in an Undergraduate Economics or Operations Management Course

ERIC Educational Resources Information Center

Naidu, Jaideep T.; Sanford, John F.

2012-01-01

Learning Curves has its roots in economics and behavioral psychology. Learning Curves theory has several business applications and is widely used in the industry. As faculty of Operations Management courses, we cover this topic in some depth in the classroom. In this paper, we present some of our teaching methods and material that have helped us…

Learning curves for transapical transcatheter aortic valve replacement in the PARTNER-I trial: Technical performance, success, and safety.

PubMed

Suri, Rakesh M; Minha, Sa'ar; Alli, Oluseun; Waksman, Ron; Rihal, Charanjit S; Satler, Lowell P; Greason, Kevin L; Torguson, Rebecca; Pichard, Augusto D; Mack, Michael; Svensson, Lars G; Rajeswaran, Jeevanantham; Lowry, Ashley M; Ehrlinger, John; Mick, Stephanie L; Tuzcu, E Murat; Thourani, Vinod H; Makkar, Raj; Holmes, David; Leon, Martin B; Blackstone, Eugene H

2016-09-01

Introduction of hybrid techniques, such as transapical transcatheter aortic valve replacement (TA-TAVR), requires skills that a heart team must master to achieve technical efficiency: the technical performance learning curve. To date, the learning curve for TA-TAVR remains unknown. We therefore evaluated the rate at which technical performance improved, assessed change in occurrence of adverse events in relation to technical performance, and determined whether adverse events after TA-TAVR were linked to acquiring technical performance efficiency (the learning curve). From April 2007 to February 2012, 1100 patients, average age 85.0 ± 6.4 years, underwent TA-TAVR in the PARTNER-I trial. Learning curves were defined by institution-specific patient sequence number using nonlinear mixed modeling. Mean procedure time decreased from 131 to 116 minutes within 30 cases (P = .06) and device success increased to 90% by case 45 (P = .0007). Within 30 days, 354 patients experienced a major adverse event (stroke in 29, death in 96), with possibly decreased complications over time (P ∼ .08). Although longer procedure time was associated with more adverse events (P < .0001), these events were associated with change in patient risk profile, not the technical performance learning curve (P = .8). The learning curve for TA-TAVR was 30 to 45 procedures performed, and technical efficiency was achieved without compromising patient safety. Although fewer patients are now undergoing TAVR via nontransfemoral access, understanding TA-TAVR learning curves and their relationship with outcomes is important as the field moves toward next-generation devices, such as those to replace the mitral valve, delivered via the left ventricular apex. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Learning micro incision surgery without the learning curve

PubMed Central

Navin, Shoba; Parikh, Rajul

2008-01-01

We describe a method of learning micro incision cataract surgery painlessly with the minimum of learning curves. A large-bore or standard anterior chamber maintainer (ACM) facilitates learning without change of machine or preferred surgical technique. Experience with the use of an ACM during phacoemulsification is desirable. PMID:18292624

Comparison of Learning Curves for Major and Minor Laparoscopic Liver Resection.

PubMed

Lee, Woohyung; Woo, Jung-Woo; Lee, Jin-Kwon; Park, Ji-Ho; Kim, Ju-Yeon; Kwag, Seung-Jin; Park, Taejin; Jeong, Sang-Ho; Ju, Young-Tae; Jeong, Eun-Jung; Lee, Young-Joon; Choi, Sang-Kyung; Hong, Soon-Chan; Jeong, Chi-Young

2016-06-01

Because laparoscopic liver resection (LLR) has a steep learning curve, analyzing experience is important for trainees. Several authors have described the learning curve of LLR, without comparing the learning curves between major and minor LLR. Perioperative data were retrieved from the medical records of 170 consecutive patients who underwent LLR by a single surgeon at a tertiary hospital. Learning curves were generated and compared between major and minor LLR using cumulative sum control charts and the moving average. Major and minor LLR was performed in 96 and 74 patients, respectively. The learning curves showed a steady state after case 50 for major LLR. Because of discordant results in minor LLR, subgroup analyses were performed, showing competency in LLR after cases 25 and 35 for left lateral sectionectomy and tumorectomy, respectively. Transfused red blood cell volume (0.6 versus 2.2 packs, P < .001) decreased after achievement of competence in major LLR. Blood loss exceeding 500 mL (odds ratio 2.395, 95% confidence interval 1.096-5.233, P = .028) was independently associated with LLR failure. The number of cases required to accomplish LLR differed according to the extent of resection. Extensive blood loss was independently associated with LLR failure.

Learning Curve of the Application of Huang Three-Step Maneuver in a Laparoscopic Spleen-Preserving Splenic Hilar Lymphadenectomy for Advanced Gastric Cancer

PubMed Central

Huang, Ze-Ning; Huang, Chang-Ming; Zheng, Chao-Hui; Li, Ping; Xie, Jian-Wei; Wang, Jia-Bin; Lin, Jian-Xian; Lu, Jun; Chen, Qi-Yue; Cao, Long-long; Lin, Mi; Tu, Ru-Hong

2016-01-01

Abstract To investigate the learning curve of the application of Huang 3-step maneuver, which was summarized and proposed by our center for the treatment of advanced upper gastric cancer. From April 2012 to March 2013, 130 consecutive patients who underwent a laparoscopic spleen-preserving splenic hilar lymphadenectomy (LSPL) by a single surgeon who performed Huang 3-step maneuver were retrospectively analyzed. The learning curve was analyzed based on the moving average (MA) method and the cumulative sum method (CUSUM). Surgical outcomes, short-term outcomes, and follow-up results before and after learning curve were contrastively analyzed. A stepwise multivariate logistic regression was used for a multivariable analysis to determine the factors that affect the operative time using Huang 3-step maneuver. Based on the CUSUM, the learning curve for Huang 3-step maneuver was divided into phase 1 (cases 1–40) and phase 2 (cases 41–130). The dissection time (DT) (P < 0.001), blood loss (BL) (P < 0.001), and number of vessels injured in phase 2 were significantly less than those in phase 1. There were no significant differences in the clinicopathological characteristics, short-term outcomes, or major postoperative complications between the learning curve phases. Univariate and multivariate analyses revealed that body mass index (BMI), short gastric vessels (SGVs), splenic hilar artery (SpA) type, and learning curve phase were significantly associated with DT. In the entire group, 124 patients were followed for a median time of 23.0 months (range, 3–30 months). There was no significant difference in the survival curve between phases. AUGC patients with a BMI less than 25 kg/m2, a small number of SGVs, and a concentrated type of SpA are ideal candidates for surgeons who are in phase 1 of the learning curve. PMID:27043698

Task complexity and maximal isometric strength gains through motor learning

PubMed Central

McGuire, Jessica; Green, Lara A.; Gabriel, David A.

2014-01-01

Abstract This study compared the effects of a simple versus complex contraction pattern on the acquisition, retention, and transfer of maximal isometric strength gains and reductions in force variability. A control group (N = 12) performed simple isometric contractions of the wrist flexors. An experimental group (N = 12) performed complex proprioceptive neuromuscular facilitation (PNF) contractions consisting of maximal isometric wrist extension immediately reversing force direction to wrist flexion within a single trial. Ten contractions were completed on three consecutive days with a retention and transfer test 2‐weeks later. For the retention test, the groups performed their assigned contraction pattern followed by a transfer test that consisted of the other contraction pattern for a cross‐over design. Both groups exhibited comparable increases in strength (20.2%, P < 0.01) and reductions in mean torque variability (26.2%, P < 0.01), which were retained and transferred. There was a decrease in the coactivation ratio (antagonist/agonist muscle activity) for both groups, which was retained and transferred (35.2%, P < 0.01). The experimental group exhibited a linear decrease in variability of the torque‐ and sEMG‐time curves, indicating transfer to the simple contraction pattern (P < 0.01). The control group underwent a decrease in variability of the torque‐ and sEMG‐time curves from the first day of training to retention, but participants returned to baseline levels during the transfer condition (P < 0.01). However, the difference between torque RMS error versus the variability in torque‐ and sEMG‐time curves suggests the demands of the complex task were transferred, but could not be achieved in a reproducible way. PMID:25428951

Machine learning models in breast cancer survival prediction.

PubMed

Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of accuracy. Therefore, this model is recommended as a useful tool for breast cancer survival prediction as well as medical decision making.

Laparoscopic varicocelectomy: virtual reality training and learning curve.

PubMed

Wang, Zheng; Ni, Yuhua; Zhang, Yinan; Jin, Xunbo; Xia, Qinghua; Wang, Hanbo

2014-01-01

To explore the role that virtual reality training might play in the learning curve of laparoscopic varicocelectomy. A total of 1326 laparoscopic varicocelectomy cases performed by 16 participants from July 2005 to June 2012 were retrospectively analyzed. The participants were divided into 2 groups: group A was trained by laparoscopic trainer boxes; group B was trained by a virtual reality training course preoperatively. The operation time curves were drafted, and the learning, improving, and platform stages were divided and statistically confirmed. The operation time and number of cases in the learning and improving stages of both groups were compared. Testicular artery sparing failure and postoperative hydroceles rate were statistically analyzed for the confirmation of the learning curve. The learning curve of laparoscopic varicocelectomy was 15 cases, and with 14 cases more, it came into the platform stage. The number of cases for the learning stages of both groups showed no statistical difference (P=.49), but the operation time of group B for the learning stage was less than that of group A (P<.00001). The number of cases of group B for the improving stage was significantly less than that of group A (P=.005), but the operation time of both groups in the improving stage showed no difference (P=.30). The difference of testicular artery sparing failure rates among these 3 stages was proved significant (P<.0001), the postoperative hydroceles rate showed no statistical difference (P=.60). The virtual reality training shortened the operation time in the learning stage and hastened the trainees' steps in the improving stage, but did not shorten the learning curve as expected to.

Mentorship, learning curves, and balance.

PubMed

Cohen, Meryl S; Jacobs, Jeffrey P; Quintessenza, James A; Chai, Paul J; Lindberg, Harald L; Dickey, Jamie; Ungerleider, Ross M

2007-09-01

Professionals working in the arena of health care face a variety of challenges as their careers evolve and develop. In this review, we analyze the role of mentorship, learning curves, and balance in overcoming challenges that all such professionals are likely to encounter. These challenges can exist both in professional and personal life. As any professional involved in health care matures, complex professional skills must be mastered, and new professional skills must be acquired. These skills are both technical and judgmental. In most circumstances, these skills must be learned. In 2007, despite the continued need for obtaining new knowledge and learning new skills, the professional and public tolerance for a "learning curve" is much less than in previous decades. Mentorship is the key to success in these endeavours. The success of mentorship is two-sided, with responsibilities for both the mentor and the mentee. The benefits of this relationship must be bidirectional. It is the responsibility of both the student and the mentor to assure this bidirectional exchange of benefit. This relationship requires time, patience, dedication, and to some degree selflessness. This mentorship will ultimately be the best tool for mastering complex professional skills and maturing through various learning curves. Professional mentorship also requires that mentors identify and explicitly teach their mentees the relational skills and abilities inherent in learning the management of the triad of self, relationships with others, and professional responsibilities.Up to two decades ago, a learning curve was tolerated, and even expected, while professionals involved in healthcare developed the techniques that allowed for the treatment of previously untreatable diseases. Outcomes have now improved to the point that this type of learning curve is no longer acceptable to the public. Still, professionals must learn to perform and develop independence and confidence. The responsibility to meet this challenge without a painful learning curve belongs to both the younger professionals, who must progress through the learning curve, and the more mature professionals who must create an appropriate environment for learning. In addition to mentorship, the detailed tracking of outcomes is an essential tool for mastering any learning curve. It is crucial to utilize a detailed database to track outcomes, to learn, and to protect both yourself and your patients. It is our professional responsibility to engage in self-evaluation, in part employing voluntary sharing of data. For cardiac surgical subspecialties, the databases now existing for The European Association for CardioThoracic Surgery and The Society of Thoracic Surgeons represent the ideal tool for monitoring outcomes. Evolving initiatives in the fields of paediatric cardiology, paediatric critical care, and paediatric cardiac anaesthesia will play similar roles.A variety of professional and personal challenges must be met by all those working in health care. The acquisition of learned skills, and the use of special tools, will facilitate the process of conquering these challenges. Choosing appropriate role models and mentors can help progression through any learning curve in a controlled and protected fashion. Professional and personal satisfaction are both necessities. Finding the satisfactory balance between work and home life is difficult, but possible with the right tools, organization skills, and support system at work and at home. The concepts of mentorship, learning curves and balance cannot be underappreciated.

Growth Patterns of Neuropsychological Functions in Indian Children

PubMed Central

Kar, Bhoomika R.; Rao, Shobini L.; Chandramouli, B. A.; Thennarasu, K.

2011-01-01

We investigated age-related differences in neuropsychological performance in 400 Indian school children (5–15 years of age). Functions of motor speed, attention, executive functions, visuospatial functions, comprehension, learning, and memory were examined. Growth curve analysis was performed. Different growth models fitted different cognitive functions. Neuropsychological task performance improved slowly between 5 and 7 years, moderately between 8 and 12 years and slowly between 13 and 15 years of age. The overall growth patterns of neuropsychological functions in Indian children have been discussed with the findings reported on American children. The present work describes non-linear, heterogeneous, and protracted age trends of neuropsychological functions in Indian children and adolescents. PMID:22053158

Comparison of the Operative Outcomes and Learning Curves between Laparoscopic and Robotic Gastrectomy for Gastric Cancer

PubMed Central

Huang, Kuo-Hung; Lan, Yuan-Tzu; Fang, Wen-Liang; Chen, Jen-Hao; Lo, Su-Shun; Li, Anna Fen-Yau; Chiou, Shih-Hwa; Wu, Chew-Wun; Shyr, Yi-Ming

2014-01-01

Background Minimally invasive surgery, including laparoscopic and robotic gastrectomy, has become more popular in the treatment of gastric cancer. However, few studies have compared the learning curves between laparoscopic and robotic gastrectomy for gastric cancer. Methods Data were prospectively collected between July 2008 and Aug 2014. A total of 145 patients underwent minimally invasive gastrectomy for gastric cancer by a single surgeon, including 73 laparoscopic and 72 robotic gastrectomies. The clinicopathologic characteristics, operative outcomes and learning curves were compared between the two groups. Results Compared with the laparoscopic group, the robotic group was associated with less blood loss and longer operative time. After the surgeon learning curves were overcome for each technique, the operative outcomes became similar between the two groups except longer operative time in the robotic group. After accumulating more cases of robotic gastrectomy, the operative time in the laparoscopic group decreased dramatically. Conclusions After overcoming the learning curves, the operative outcomes became similar between laparoscopic and robotic gastrectomy. The experience of robotic gastrectomy could affect the learning process of laparoscopic gastrectomy. PMID:25360767

Diatomic predissociation line widths

NASA Technical Reports Server (NTRS)

Child, M. S.

1973-01-01

Predissociation by rotation and curve crossing in diatomic molecules is discussed. The pattern of predissociation line widths is seen as providing a highly sensitive yardstick for the determination of unknown potential curves. In addition, the computation of such a pattern for given potential curves is considered a matter of routine, unless the predissociation happens to occur from an adiabatic potential curve. Analytic formulas are used to provide physical insight into the details of the predissociation pattern, to the extent that a direct inversion procedure is developed for determination of the repulsive potential curves for Type 1 predissociations.

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

PubMed Central

Tabelow, Karsten; König, Reinhard; Polzehl, Jörg

2016-01-01

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

PubMed

Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

2018-05-01

A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

Space Communications Artificial Intelligence for Link Evaluation Terminal (SCAILET)

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh

1991-01-01

A software application to assis end-users of the Link Evaluation Terminal (LET) for satellite communication is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving, 220/110 Mbps capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET and ACTS are being developed at the NASA Lewis Research Center. The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. By comparing the transmitted bit pattern with the received bit pattern, HBR LET can determine the bit error rate BER) under various atmospheric conditions. An algorithm for power augmentation is applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions. Programming scripts, defined by the design engineer, set up the HBR LET terminal by programming subsystem devices through IEEE488 interfaces. However, the scripts are difficult to use, require a steep learning curve, are cryptic, and are hard to maintain. The combination of the learning curve and the complexities involved with editing the script files may discourage end-users from utilizing the full capabilities of the HBR LET system. An intelligent assistant component of SCAILET that addresses critical end-user needs in the programming of the HBR LET system as anticipated by its developers is described. A close look is taken at the various steps involved in writing ECM software for a C&P, computer and at how the intelligent assistant improves the HBR LET system and enhances the end-user's ability to perform the experiments.

Preliminary experience and learning curve for laparoendoscopic single-site retroperitoneal pyeloplasty.

PubMed

Ou, Zhenyu; Qi, Lin; Yang, Jinrui; Chen, Xiang; Cao, Zhenzhen; Zu, Xiongbing; Liu, Longfei; Wang, Long

2013-09-01

To report our preliminary experience and to assess the learning curve for laparoendoscopic single-site retroperitoneal pyeloplasty (LESS-RP) for ureteropelvic junction obstruction (UPJO). From July 2010 to February 2012, LESS-RP was performed in 27 patients affected with UPJO by a single surgeon. A homemade single-access platform and both conventional and prebent instruments were applied. Patient characteristics and perioperative outcomes were analyzed. The cumulative sum (CUSUM) method was used to evaluate the learning curve. The LESS-RP was successfully accomplished in all 27 patients. The mean operative time (OT) was 175.9±22.5 minutes, and the mean estimated blood loss was 83.3±27.1 mL. We used the OT as a proxy to assess the learning curve. The CUSUM learning curve can be divided into two distinct phases: the initial 12 cases and the last 15 cases. There were significant differences in the mean OT (195.6 minutes versus 159.1 minutes, P<.001) and mean estimated blood loss (97.2 mL versus 72.2 mL, P=.014) between the two phases. The two phases did not differ in other parameters. LESS-RP is a safe and feasible procedure. The learning curve of a single surgeon suggests that the initial learning phase for LESS-RP can be completed after approximately 12 cases.

Hysteroscopic sterilization using a virtual reality simulator: assessment of learning curve.

PubMed

Janse, Juliënne A; Goedegebuure, Ruben S A; Veersema, Sebastiaan; Broekmans, Frank J M; Schreuder, Henk W R

2013-01-01

To assess the learning curve using a virtual reality simulator for hysteroscopic sterilization with the Essure method. Prospective multicenter study (Canadian Task Force classification II-2). University and teaching hospital in the Netherlands. Thirty novices (medical students) and five experts (gynecologists who had performed >150 Essure sterilization procedures). All participants performed nine repetitions of bilateral Essure placement on the simulator. Novices returned after 2 weeks and performed a second series of five repetitions to assess retention of skills. Structured observations on performance using the Global Rating Scale and parameters derived from the simulator provided measurements for analysis. The learning curve is represented by improvement per procedure. Two-way repeated-measures analysis of variance was used to analyze learning curves. Effect size (ES) was calculated to express the practical significance of the results (ES ≥ 0.50 indicates a large learning effect). For all parameters, significant improvements were found in novice performance within nine repetitions. Large learning effects were established for six of eight parameters (p < .001; ES, 0.50-0.96). Novices approached expert level within 9 to 14 repetitions. The learning curve established in this study endorses future implementation of the simulator in curricula on hysteroscopic skill acquisition for clinicians who are interested in learning this sterilization technique. Copyright © 2013 AAGL. Published by Elsevier Inc. All rights reserved.

Learning curve evaluation using cumulative summation analysis-a clinical example of pediatric robot-assisted laparoscopic pyeloplasty.

PubMed

Cundy, Thomas P; Gattas, Nicholas E; White, Alan D; Najmaldin, Azad S

2015-08-01

The cumulative summation (CUSUM) method for learning curve analysis remains under-utilized in the surgical literature in general, and is described in only a small number of publications within the field of pediatric surgery. This study introduces the CUSUM analysis technique and applies it to evaluate the learning curve for pediatric robot-assisted laparoscopic pyeloplasty (RP). Clinical data were prospectively recorded for consecutive pediatric RP cases performed by a single-surgeon. CUSUM charts and tests were generated for set-up time, docking time, console time, operating time, total operating room time, and postoperative complications. Conversions and avoidable operating room delay were separately evaluated with respect to case experience. Comparisons between case experience and time-based outcomes were assessed using the Student's t-test and ANOVA for bi-phasic and multi-phasic learning curves respectively. Comparison between case experience and complication frequency was assessed using the Kruskal-Wallis test. A total of 90 RP cases were evaluated. The learning curve transitioned beyond the learning phase at cases 10, 15, 42, 57, and 58 for set-up time, docking time, console time, operating time, and total operating room time respectively. All comparisons of mean operating times between the learning phase and subsequent phases were statistically significant (P=<0.001-0.01). No significant difference was observed between case experience and frequency of post-operative complications (P=0.125), although the CUSUM chart demonstrated a directional change in slope for the last 12 cases in which there were high proportions of re-do cases and patients <6 months of age. The CUSUM method has a valuable role for learning curve evaluation and outcome quality monitoring. In applying this statistical technique to the largest reported single surgeon series of pediatric RP, we demonstrate numerous distinctly shaped learning curves and well-defined learning phase transition points. Copyright © 2015 Elsevier Inc. All rights reserved.

Assessment of Surgical Learning Curves in Transoral Robotic Surgery for Squamous Cell Carcinoma of the Oropharynx

PubMed Central

Albergotti, William G.; Gooding, William E.; Kubik, Mark W.; Geltzeiler, Mathew; Kim, Seungwon; Duvvuri, Umamaheswar; Ferris, Robert L.

2017-01-01

IMPORTANCE Transoral robotic surgery (TORS) is increasingly employed as a treatment option for squamous cell carcinoma of the oropharynx (OPSCC). Measures of surgical learning curves are needed particularly as clinical trials using this technology continue to evolve. OBJECTIVE To assess learning curves for the oncologic TORS surgeon and to identify the number of cases needed to identify the learning phase. DESIGN, SETTING, AND PARTICIPANTS A retrospective review of all patients who underwent TORS for OPSCC at the University of Pittsburgh Medical Center between March 2010 and March 2016. Cases were excluded for involvement of a subsite outside of the oropharynx, for nonmalignant abnormality or nonsquamous histology, unknown primary, no tumor in the main specimen, free flap reconstruction, and for an inability to define margin status. EXPOSURES Transoral robotic surgery for OPSCC. MAIN OUTCOMES AND MEASURES Primary learning measures defined by the authors include the initial and final margin status and time to resection of main surgical specimen. A cumulative sum learning curve was developed for each surgeon for each of the study variables. The inflection point of each surgeon’s curve was considered to be the point signaling the completion of the learning phase. RESULTS There were 382 transoral robotic procedures identified. Of 382 cases, 160 met our inclusion criteria: 68 for surgeon A, 37 for surgeon B, and 55 for surgeon C. Of the 160 included patients, 125 were men and 35 were women. The mean (SD) age of participants was 59.4 (9.5) years. Mean (SD) time to resection including robot set-up was 79 (36) minutes. The inflection points for the final margin status learning curves were 27 cases (surgeon A) and 25 cases (surgeon C). There was no inflection point for surgeon B for final margin status. Inflection points for mean time to resection were: 39 cases (surgeon A), 30 cases (surgeon B), and 27 cases (surgeon C). CONCLUSIONS AND RELEVANCE Using metrics of positive margin rate and time to resection of the main surgical specimen, the learning curve for TORS for OPSCC is surgeon-specific. Inflection points for most learning curves peak between 20 and 30 cases. PMID:28196200

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

PubMed

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L; Bilello, Michel; O'Rourke, Donald M; Davatzikos, Christos

2016-03-01

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

ERIC Educational Resources Information Center

Hsu, Pi-Shan

2012-01-01

This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

Learning curve for intracranial angioplasty and stenting in single center.

PubMed

Cai, Qiankun; Li, Yongkun; Xu, Gelin; Sun, Wen; Xiong, Yunyun; Sun, Wenshan; Bao, Yuanfei; Huang, Xianjun; Zhang, Yao; Zhou, Lulu; Zhu, Wusheng; Liu, Xinfeng

2014-01-01

To identify the specific caseload to overcome learning curve effect based on data from consecutive patients treated with Intracranial Angioplasty and Stenting (IAS) in our center. The Stenting and Aggressive Medical Management for Preventing Recurrent Stroke and Intracranial Stenosis trial was prematurely terminated owing to the high rate of periprocedural complications in the endovascular arm. To date, there are no data available for determining the essential caseload sufficient to overcome the learning effect and perform IAS with an acceptable level of complications. Between March 2004 and May 2012, 188 consecutive patients with 194 lesions who underwent IAS were analyzed retrospectively. The outcome variables used to assess the learning curve were periprocedural complications (included transient ischemic attack, ischemic stroke, vessel rupture, cerebral hyperperfusion syndrome, and vessel perforation). Multivariable logistic regression analysis was employed to illustrate the existence of learning curve effect on IAS. A risk-adjusted cumulative sum chart was performed to identify the specific caseload to overcome learning curve effect. The overall rate of 30-days periprocedural complications was 12.4% (24/194). After adjusting for case-mix, multivariate logistic regression analysis showed that operator experience was an independent predictor for periprocedural complications. The learning curve of IAS to overcome complications in a risk-adjusted manner was 21 cases. Operator's level of experience significantly affected the outcome of IAS. Moreover, we observed that the amount of experience sufficient for performing IAS in our center was 21 cases. Copyright © 2013 Wiley Periodicals, Inc.

A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs

DOE PAGES

Smith, Sarah Josephine; Wei, Max; Sohn, Michael D.

2016-09-17

Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North Americanmore » datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate.« less

A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Sarah Josephine; Wei, Max; Sohn, Michael D.

Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North Americanmore » datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate.« less

Multiple Optical Traps with a Single-Beam Optical Tweezer Utilizing Surface Micromachined Planar Curved Grating

NASA Astrophysics Data System (ADS)

Kuo, Ju-Nan; Chen, Kuan-Yu

2010-11-01

In this paper, we present a single-beam optical tweezer integrated with a planar curved diffraction grating for microbead manipulation. Various curvatures of the surface micromachined planar curved grating are systematically investigated. The planar curved grating was fabricated using multiuser micro-electro-mechanical-system (MEMS) processes (MUMPs). The angular separation and the number of diffracted orders were determined. Experimental results indicate that the diffraction patterns and curvature of the planar curved grating are closely related. As the curvature of the planar curved grating increases, the vertical diffraction angle increases, resulting in the strip patterns of the planar curved grating. A single-beam optical tweezer integrated with a planar curved diffraction grating was developed. We demonstrate a technique for creating multiple optical traps from a single laser beam using the developed planar curved grating. The strip patterns of the planar curved grating that resulted from diffraction were used to trap one row of polystyrene beads.

Acquisition Challenge: The Importance of Incompressibility in Comparing Learning Curve Models

DTIC Science & Technology

2015-10-01

parameters for all four learning mod- els used in the study . The learning rate factor, b, is the slope of the linear regression line, which in this case is...incorporated within the DoD acquisition environment. This study tested three alternative learning models (the Stanford-B model, DeJong’s learning formula...appropriate tools to calculate accurate and reliable predictions. However, conventional learning curve methodology has been in practice since the pre

A Primer on the Statistical Modelling of Learning Curves in Health Professions Education

ERIC Educational Resources Information Center

Pusic, Martin V.; Boutis, Kathy; Pecaric, Martin R.; Savenkov, Oleksander; Beckstead, Jason W.; Jaber, Mohamad Y.

2017-01-01

Learning curves are a useful way of representing the rate of learning over time. Features include an index of baseline performance (y-intercept), the efficiency of learning over time (slope parameter) and the maximal theoretical performance achievable (upper asymptote). Each of these parameters can be statistically modelled on an individual and…

Learning curve in robotic rectal cancer surgery: current state of affairs.

PubMed

Jiménez-Rodríguez, Rosa M; Rubio-Dorado-Manzanares, Mercedes; Díaz-Pavón, José Manuel; Reyes-Díaz, M Luisa; Vazquez-Monchul, Jorge Manuel; Garcia-Cabrera, Ana M; Padillo, Javier; De la Portilla, Fernando

2016-12-01

Robotic-assisted rectal cancer surgery offers multiple advantages for surgeons, and it seems to yield the same clinical outcomes as regards the short-time follow-up of patients compared to conventional laparoscopy. This surgical approach emerges as a technique aiming at overcoming the limitations posed by rectal cancer and other surgical fields of difficult access, in order to obtain better outcomes and a shorter learning curve. A systematic review of the literature of robot-assisted rectal surgery was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search was conducted in October 2015 in PubMed, MEDLINE and the Cochrane Central Register of Controlled Trials, for articles published in the last 10 years and pertaining the learning curve of robotic surgery for colorectal cancer. It consisted of the following key words: "rectal cancer/learning curve/robotic-assisted laparoscopic surgery". A total of 34 references were identified, but only 9 full texts specifically addressed the analysis of the learning curve in robot-assisted rectal cancer surgery, 7 were case series and 2 were non-randomised case-comparison series. Eight papers used the cumulative sum (CUSUM) method, and only one author divided the series into two groups to compare both. The mean number of cases for phase I of the learning curve was calculated to be 29.7 patients; phase II corresponds to a mean number 37.4 patients. The mean number of cases required for the surgeon to be classed as an expert in robotic surgery was calculated to be 39 patients. Robotic advantages could have an impact on learning curve for rectal cancer and lower the number of cases that are necessary for rectal resections.

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system.

PubMed

Kaplan, Bernhard A; Lansner, Anders

2014-01-01

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin-Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian-Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian-Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures.

A spiking neural network model of self-organized pattern recognition in the early mammalian olfactory system

PubMed Central

Kaplan, Bernhard A.; Lansner, Anders

2014-01-01

Olfactory sensory information passes through several processing stages before an odor percept emerges. The question how the olfactory system learns to create odor representations linking those different levels and how it learns to connect and discriminate between them is largely unresolved. We present a large-scale network model with single and multi-compartmental Hodgkin–Huxley type model neurons representing olfactory receptor neurons (ORNs) in the epithelium, periglomerular cells, mitral/tufted cells and granule cells in the olfactory bulb (OB), and three types of cortical cells in the piriform cortex (PC). Odor patterns are calculated based on affinities between ORNs and odor stimuli derived from physico-chemical descriptors of behaviorally relevant real-world odorants. The properties of ORNs were tuned to show saturated response curves with increasing concentration as seen in experiments. On the level of the OB we explored the possibility of using a fuzzy concentration interval code, which was implemented through dendro-dendritic inhibition leading to winner-take-all like dynamics between mitral/tufted cells belonging to the same glomerulus. The connectivity from mitral/tufted cells to PC neurons was self-organized from a mutual information measure and by using a competitive Hebbian–Bayesian learning algorithm based on the response patterns of mitral/tufted cells to different odors yielding a distributed feed-forward projection to the PC. The PC was implemented as a modular attractor network with a recurrent connectivity that was likewise organized through Hebbian–Bayesian learning. We demonstrate the functionality of the model in a one-sniff-learning and recognition task on a set of 50 odorants. Furthermore, we study its robustness against noise on the receptor level and its ability to perform concentration invariant odor recognition. Moreover, we investigate the pattern completion capabilities of the system and rivalry dynamics for odor mixtures. PMID:24570657

Is the lumbar modifier useful in surgical decision making?: defining two distinct Lenke 1A curve patterns.

PubMed

Miyanji, Firoz; Pawelek, Jeff B; Van Valin, Scott E; Upasani, Vidyadhar V; Newton, Peter O

2008-11-01

Retrospective review of adolescent idiopathic scoliosis (AIS) patients. To investigate the clinical deformity and radiographic features of Lenke 1A and 1B curves to determine if the "A" and "B" lumbar modifiers actually describe 2 distinct curve patterns. The Lenke classification system attempts to address some of the shortcomings of the King-Moe classification system by providing a more comprehensive, reliable, and treatment-based categorization of all AIS deformities. Although this classification is useful in determining which regions of the spine should be fused, it does not necessarily divide AIS curves into distinct patterns. A critical analysis of the clinical deformity, radiographic features, and surgical treatment of AIS patients with Lenke 1A and 1B right thoracic curves was performed. Lenke 1A curves were differentiated according to the L4 coronal plane tilt. Analysis of variance and Pearson chi analysis were used to perform statistical comparisons between the individual curve patterns (P < or = 0.05). Ninety-three patients with preoperative and 2-year postoperative data were included in this analysis (65 Lenke 1A, and 28 Lenke 1B). Thirty-three patients were subdivided as 1A-L (L4 tilted to the left) and 32 patients were subdivided as 1A-R (L4 tilted to the right). The interobserver reliability for determining the direction of L4 tilt was excellent (kappa = 0.94, P < or = 0.001). Patients with 1A-L curves were similar to patients with 1B curves with respect to the L4 tilt and the location of the stable vertebra (most often in the thoracolumbar junction). In contrast, patients with 1A-R curves had a more distal stable vertebra (most often L3 or L4). The surgical treatment also differed between these 2 groups with regards to the lowest instrumented vertebra (LIV). 1A-L and 1B curves were similar with a median LIV of T12, whereas the 1A-R curves had a more distal median LIV of L2 (P = 0.01). Two Lenke 1A curve patterns can be described based on the direction of the L4 tilt. This distinction has ramifications regarding selection of fusion levels and assessing surgical outcomes. The A and B lumbar modifiers do not describe 2 distinct curve types within the Lenke 1 group; however, the tilt direction of L4 does allow subdivision of the Lenke 1A curves into 2 distinguishable patterns (1A-R and 1A-L). The 1A-L curves are similar to 1B curves and different in form and treatment from the 1A-R pattern.

Establishing the Learning Curve of Robotic Sacral Colpopexy in a Start-up Robotics Program.

PubMed

Sharma, Shefali; Calixte, Rose; Finamore, Peter S

2016-01-01

To determine the learning curve of the following segments of a robotic sacral colpopexy: preoperative setup, operative time, postoperative transition, and room turnover. A retrospective cohort study to determine the number of cases needed to reach points of efficiency in the various segments of a robotic sacral colpopexy (Canadian Task Force II-2). A university-affiliated community hospital. Women who underwent robotic sacral colpopexy at our institution from 2009 to 2013 comprise the study population. Patient characteristics and operative reports were extracted from a patient database that has been maintained since the inception of the robotics program at Winthrop University Hospital and electronic medical records. Based on additional procedures performed, 4 groups of patients were created (A-D). Learning curves for each of the segment times of interest were created using penalized basis spline (B-spline) regression. Operative time was further analyzed using an inverse curve and sequential grouping. A total of 176 patients were eligible. Nonparametric tests detected no difference in procedure times between the 4 groups (A-D) of patients. The preoperative and postoperative points of efficiency were 108 and 118 cases, respectively. The operative points of proficiency and efficiency were 25 and 36 cases, respectively. Operative time was further analyzed using an inverse curve that revealed that after 11 cases the surgeon had reached 90% of the learning plateau. Sequential grouping revealed no significant improvement in operative time after 60 cases. Turnover time could not be assessed because of incomplete data. There is a difference in the operative time learning curve for robotic sacral colpopexy depending on the statistical analysis used. The learning curve of the operative segment showed an improvement in operative time between 25 and 36 cases when using B-spline regression. When the data for operative time was fit to an inverse curve, a learning rate of 11 cases was appreciated. Using sequential grouping to describe the data, no improvement in operative time was seen after 60 cases. Ultimately, we believe that efficiency in operative time is attained after 30 to 60 cases when performing robotic sacral colpopexy. The learning curve for preoperative setup and postoperative transition, which is reflective of anesthesia and nursing staff, was approximately 110 cases. Copyright © 2016 AAGL. Published by Elsevier Inc. All rights reserved.

Learning Curve for Seawater Reverse Osmosis Desalination Plants: Capital Cost Trend of the Past, Present, and Future

NASA Astrophysics Data System (ADS)

Caldera, Upeksha; Breyer, Christian

2017-12-01

Seawater reverse osmosis (SWRO) desalination is expected to play a pivotal role in helping to secure future global water supply. While the global reliance on SWRO plants for water security increases, there is no consensus on how the capital costs of SWRO plants will vary in the future. The aim of this paper is to analyze the past trends of the SWRO capital expenditures (capex) as the historic global cumulative online SWRO capacity increases, based on the learning curve concept. The SWRO capex learning curve is found based on 4,237 plants that came online from 1977 to 2015. A learning rate of 15% is determined, implying that the SWRO capex reduced by 15% when the cumulative capacity was doubled. Based on SWRO capacity annual growth rates of 10% and 20%, by 2030, the global average capex of SWRO plants is found to fall to 1,580 USD/(m3/d) and 1,340 USD/(m3/d), respectively. A learning curve for SWRO capital costs has not been presented previously. This research highlights the potential for decrease in SWRO capex with the increase in installation of SWRO plants and the value of the learning curve approach to estimate future SWRO capex.

Relationship between spontaneous expiratory flow-volume curve pattern and air-flow obstruction in elderly COPD patients.

PubMed

Nozoe, Masafumi; Mase, Kyoshi; Murakami, Shigefumi; Okada, Makoto; Ogino, Tomoyuki; Matsushita, Kazuhiro; Takashima, Sachie; Yamamoto, Noriyasu; Fukuda, Yoshihiro; Domen, Kazuhisa

2013-10-01

Assessment of the degree of air-flow obstruction is important for determining the treatment strategy in COPD patients. However, in some elderly COPD patients, measuring FVC is impossible because of cognitive dysfunction or severe dyspnea. In such patients a simple test of airways obstruction requiring only a short run of tidal breathing would be useful. We studied whether the spontaneous expiratory flow-volume (SEFV) curve pattern reflects the degree of air-flow obstruction in elderly COPD patients. In 34 elderly subjects (mean ± SD age 80 ± 7 y) with stable COPD (percent-of-predicted FEV(1) 39.0 ± 18.5%), and 12 age-matched healthy subjects, we measured FVC and recorded flow-volume curves during quiet breathing. We studied the SEFV curve patterns (concavity/convexity), spirometry results, breathing patterns, and demographics. The SEFV curve concavity/convexity prediction accuracy was examined by calculating the receiver operating characteristic curves, cutoff values, area under the curve, sensitivity, and specificity. Fourteen subjects with COPD had a concave SEFV curve. All the healthy subjects had convex SEFV curves. The COPD subjects who had concave SEFV curves often had very severe airway obstruction. The percent-of-predicted FEV(1)% (32.4%) was the most powerful SEFV curve concavity predictor (area under the curve 0.92, 95% CI 0.83-1.00), and had the highest sensitivity (0.93) and specificity (0.88). Concavity of the SEFV curve obtained during tidal breathing may be a useful test for determining the presence of very severe obstruction in elderly patients unable to perform a satisfactory FVC maneuver.

Defining the learning curve in laparoscopic paraesophageal hernia repair: a CUSUM analysis.

PubMed

Okrainec, Allan; Ferri, Lorenzo E; Feldman, Liane S; Fried, Gerald M

2011-04-01

There are numerous reports in the literature documenting high recurrence rates after laparoscopic paraesophageal hernia repair. The purpose of this study was to determine the learning curve for this procedure using the Cumulative Summation (CUSUM) technique. Forty-six consecutive patients with paraesophageal hernia were evaluated prospectively after laparoscopic paraesophageal hernia repair. Upper GI series was performed 3 months postoperatively to look for recurrence. Patients were stratified based on the surgeon's early (first 20 cases) and late experience (>20 cases). The CUSUM method was then used to further analyze the learning curve. Nine patients (21%) had anatomic recurrence. There was a trend toward a higher recurrence rate during the first 20 cases, although this did not achieve statistical significance (33% vs. 13%, p = 0.10). However, using a CUSUM analysis to plot the learning curve, we found that the recurrence rate diminishes after 18 cases and reaches an acceptable rate after 26 cases. Surgeon experience is an important predictor of recurrence after laparoscopic paraesophageal hernia repair. CUSUM analysis revealed there is a significant learning curve to become proficient at this procedure, with approximately 20 cases required before a consistent decrease in hernia recurrence rate is observed.

Improving vulnerability models: lessons learned from a comparison between flood and earthquake assessments

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen; Ward, Philip; Daniell, James; Aerts, Jeroen

2017-04-01

In a cross-discipline study, an extensive literature review has been conducted to increase the understanding of vulnerability indicators used in both earthquake- and flood vulnerability assessments, and to provide insights into potential improvements of earthquake and flood vulnerability assessments. It identifies and compares indicators used to quantitatively assess earthquake and flood vulnerability, and discusses their respective differences and similarities. Indicators have been categorized into Physical- and Social categories, and further subdivided into (when possible) measurable and comparable indicators. Physical vulnerability indicators have been differentiated to exposed assets such as buildings and infrastructure. Social indicators are grouped in subcategories such as demographics, economics and awareness. Next, two different vulnerability model types have been described that use these indicators: index- and curve-based vulnerability models. A selection of these models (e.g. HAZUS) have been described, and compared on several characteristics such as temporal- and spatial aspects. It appears that earthquake vulnerability methods are traditionally strongly developed towards physical attributes at an object scale and used in vulnerability curve models, whereas flood vulnerability studies focus more on indicators applied to aggregated land-use scales. Flood risk studies could be improved using approaches from earthquake studies, such as incorporating more detailed lifeline and building indicators, and developing object-based vulnerability curve assessments of physical vulnerability, for example by defining building material based flood vulnerability curves. Related to this, is the incorporation of time of the day based building occupation patterns (at 2am most people will be at home while at 2pm most people will be in the office). Earthquake assessments could learn from flood studies when it comes to the refined selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies to further explore cross-hazard studies.

Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques.

PubMed

Cook, Diane J; Schmitter-Edgecombe, Maureen; Dawadi, Prafulla

2015-11-01

One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while ( n = 84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an area under the ROC curve value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant.

Comparison of different sets of instruments for laparoendoscopic single-site surgery in a surgical simulator with novices.

PubMed

Wang, Dong; Shi, Long-Qing; Wang, Jing-Min; Jiang, Xiao-Hua; Ji, Zhen-Ling

2016-04-01

Given the parallel entry of working instruments through a single incision in laparoendoscopic single-site surgery, loss of triangulation in the abdominal cavity and counteracting movements of the instruments are inevitable obstacles. Some specially designed devices have emerged to ameliorate these challenges. Twenty-four novice participants were randomized into four groups using assigned instruments, conventional straight instruments, single-curved instruments, double-curved instruments and articulating instruments, respectively, to perform two basic tasks (peg transferring and pattern cutting) 14 times in a modified simulator. A test of the tasks and a resection of the intestine segment of a rat were performed. The task scores and evaluation of intraoperative skills during the resection of the intestine segment were recorded. The instrument of modified National Aeronautics and Space Administration Task Load Index (NASA-TLX) was completed. The task scores of the groups using single-curved instruments and articulating instruments were better than the other two groups on the simulator tasks, consistent with the evaluation of intraoperative skills during the resection of intestine segment. As the proficiency with the instruments increased, the task scores improved, as demonstrated by the learning curve. The workload measured by the modified NASA-TLX tool demonstrated that the groups using articulating instruments and double-curved instruments had a heavier workload in most of the categories compared with the other two groups. Single-curved and articulating instruments are more effective than conventional straight and double-curved devices, and are favourable in laparoendoscopic single-site surgery for novice learners. © 2013 Royal Australasian College of Surgeons.

Design and analysis of grid stiffened fuselage panel with curved stiffeners

NASA Astrophysics Data System (ADS)

Hemanth, Bharath; Babu, N. C. Mahendra; Shivakumar, H. G.; Srikari, S.

2018-04-01

Designing and analyzing grid stiffened panel to understand the effect of stiffeners on stiffness of the panel is crucial in designing grid stiffened cylinder for fuselage application. Traditionally only straight stiffeners were used due to limited manufacturing capabilities and in recent years GSS with curved stiffeners have become a reality. The present work is on flat grid stiffened panel and the focus is to realize the change in stiffness by converting straight stiffeners in an isogrid panel to curved stiffeners. An isogrid stiffened panel is identified from literature for which experimental results were available and was considered for replacing straight stiffeners with curved stiffeners. Defining and designing the curve for curved stiffeners which can be used to replace straight stiffeners in isogrid pattern is crucial. FE model of the grid stiffened fuselage panel with isogrid pattern identified from the literature for which experimental data was available was developed and evaluated for stiffness. For the same panel, curved grid pattern to enhance stiffness of the panel was designed following existing design procedure. FE model of the grid stiffened fuselage panel with designed curved stiffeners was developed and evaluated for stiffness. It is established that the stiffness of panel can be increased by minimum of 2.82% to maximum of 11.93% by using curved stiffeners of particular curvature as a replacement for straight stiffeners in isogrid pattern with a slight mass penalty.

The training and learning process of transseptal puncture using a modified technique.

PubMed

Yao, Yan; Ding, Ligang; Chen, Wensheng; Guo, Jun; Bao, Jingru; Shi, Rui; Huang, Wen; Zhang, Shu; Wong, Tom

2013-12-01

As the transseptal (TS) puncture has become an integral part of many types of cardiac interventional procedures, its technique that was initial reported for measurement of left atrial pressure in 1950s, continue to evolve. Our laboratory adopted a modified technique which uses only coronary sinus catheter as the landmark to accomplishing TS punctures under fluoroscopy. The aim of this study is prospectively to evaluate the training and learning process for TS puncture guided by this modified technique. Guided by the training protocol, TS puncture was performed in 120 consecutive patients by three trainees without previous personal experience in TS catheterization and one experienced trainer as a controller. We analysed the following parameters: one puncture success rate, total procedure time, fluoroscopic time, and radiation dose. The learning curve was analysed using curve-fitting methodology. The first attempt at TS crossing was successful in 74 (82%), a second attempt was successful in 11 (12%), and 5 patients failed to puncture the interatrial septal finally. The average starting process time was 4.1 ± 0.8 min, and the estimated mean learning plateau was 1.2 ± 0.2 min. The estimated mean learning rate for process time was 25 ± 3 cases. Important aspects of learning curve can be estimated by fitting inverse curves for TS puncture. The study demonstrated that this technique was a simple, safe, economic, and effective approach for learning of TS puncture. Base on the statistical analysis, approximately 29 TS punctures will be needed for trainee to pass the steepest area of learning curve.

Neurobiological and Endocrine Correlates of Individual Differences in Spatial Learning Ability

PubMed Central

Sandi, Carmen; Cordero, M. Isabel; Merino, José J.; Kruyt, Nyika D.; Regan, Ciaran M.; Murphy, Keith J.

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former. PMID:15169853

Neurobiological and endocrine correlates of individual differences in spatial learning ability.

PubMed

Sandi, Carmen; Cordero, M Isabel; Merino, José J; Kruyt, Nyika D; Regan, Ciaran M; Murphy, Keith J

2004-01-01

The polysialylated neural cell adhesion molecule (PSA-NCAM) has been implicated in activity-dependent synaptic remodeling and memory formation. Here, we questioned whether training-induced modulation of PSA-NCAM expression might be related to individual differences in spatial learning abilities. At 12 h posttraining, immunohistochemical analyses revealed a learning-induced up-regulation of PSA-NCAM in the hippocampal dentate gyrus that was related to the spatial learning abilities displayed by rats during training. Specifically, a positive correlation was found between latency to find the platform and subsequent activated PSA levels, indicating that greater induction of polysialylation was observed in rats with the slower acquisition curve. At posttraining times when no learning-associated activation of PSA was observed, no such correlation was found. Further experiments revealed that performance in the massed water maze training is related to a pattern of spatial learning and memory abilities, and to learning-related glucocorticoid responsiveness. Taken together, our findings suggest that the learning-related neural circuits of fast learners are better suited to solving the water maze task than those of slow learners, the latter relying more on structural reorganization to form memory, rather than the relatively economic mechanism of altering synaptic efficacy that is likely used by the former.

Characterizing cartilage microarchitecture on phase-contrast x-ray computed tomography using deep learning with convolutional neural networks

NASA Astrophysics Data System (ADS)

Deng, Botao; Abidin, Anas Z.; D'Souza, Adora M.; Nagarajan, Mahesh B.; Coan, Paola; Wismüller, Axel

2017-03-01

The effectiveness of phase contrast X-ray computed tomography (PCI-CT) in visualizing human patellar cartilage matrix has been demonstrated due to its ability to capture soft tissue contrast on a micrometer resolution scale. Recent studies have shown that off-the-shelf Convolutional Neural Network (CNN) features learned from a nonmedical data set can be used for medical image classification. In this paper, we investigate the ability of features extracted from two different CNNs for characterizing chondrocyte patterns in the cartilage matrix. We obtained features from 842 regions of interest annotated on PCI-CT images of human patellar cartilage using CaffeNet and Inception-v3 Network, which were then used in a machine learning task involving support vector machines with radial basis function kernel to classify the ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area (AUC) under the Receiver Operating Characteristic (ROC) curve. The best classification performance was observed with features from Inception-v3 network (AUC = 0.95), which outperforms features extracted from CaffeNet (AUC = 0.91). These results suggest that such characterization of chondrocyte patterns using features from internal layers of CNNs can be used to distinguish between healthy and osteoarthritic tissue with high accuracy.

Robotic partial nephrectomy shortens warm ischemia time, reducing suturing time kinetics even for an experienced laparoscopic surgeon: a comparative analysis.

PubMed

Faria, Eliney F; Caputo, Peter A; Wood, Christopher G; Karam, Jose A; Nogueras-González, Graciela M; Matin, Surena F

2014-02-01

Laparoscopic and robotic partial nephrectomy (LPN and RPN) are strongly related to influence of tumor complexity and learning curve. We analyzed a consecutive experience between RPN and LPN to discern if warm ischemia time (WIT) is in fact improved while accounting for these two confounding variables and if so by which particular aspect of WIT. This is a retrospective analysis of consecutive procedures performed by a single surgeon between 2002-2008 (LPN) and 2008-2012 (RPN). Specifically, individual steps, including tumor excision, suturing of intrarenal defect, and parenchyma, were recorded at the time of surgery. Multivariate and univariate analyzes were used to evaluate influence of learning curve, tumor complexity, and time kinetics of individual steps during WIT, to determine their influence in WIT. Additionally, we considered the effect of RPN on the learning curve. A total of 146 LPNs and 137 RPNs were included. Considering renal function, WIT, suturing time, renorrhaphy time were found statistically significant differences in favor of RPN (p < 0.05). In the univariate analysis, surgical procedure, learning curve, clinical tumor size, and RENAL nephrometry score were statistically significant predictors for WIT (p < 0.05). RPN decreased the WIT on average by approximately 7 min compared to LPN even when adjusting for learning curve, tumor complexity, and both together (p < 0.001). We found RPN was associated with a shorter WIT when controlling for influence of the learning curve and tumor complexity. The time required for tumor excision was not shortened but the time required for suturing steps was significantly shortened.

Video-Assisted Thoracic Surgical Lobectomy for Lung Cancer: Description of a Learning Curve.

PubMed

Yao, Fei; Wang, Jian; Yao, Ju; Hang, Fangrong; Cao, Shiqi; Cao, Yongke

2017-07-01

Video-assisted thoracic surgical (VATS) lobectomy is gaining popularity in the treatment of lung cancer. The aim of this study is to investigate the learning curve of VATS lobectomy by using multidimensional methods and to compare the learning curve groups with respect to perioperative clinical outcomes. We retrospectively reviewed a prospective database to identify 67 consecutive patients who underwent VATS lobectomy for lung cancer by a single surgeon. The learning curve was analyzed by using moving average and the cumulative sum (CUSUM) method. With the moving average and CUSUM analyses for the operation time, patients were stratified into two groups, with chronological order defining early and late experiences. Perioperative clinical outcomes were compared between the two learning curve groups. According to the moving average method, the peak point for operation time occurred at the 26th case. The CUSUM method also showed the operation time peak point at the 26th case. When results were compared between early- and late-experience periods, the operation time, duration of chest drainage, and postoperative hospital stay were significantly longer in the early-experience group (cases 1 to 26). The intraoperative estimated blood loss was significantly less in the late-experience group (cases 27 to 67). CUSUM charts showed a decreasing duration of chest drainage after the 36th case and shortening postoperative hospital stay after the 37th case. Multidimensional statistical analyses suggested that the learning curve for VATS lobectomy for lung cancer required ∼26 cases. Favorable intraoperative and postoperative care parameters for VATS lobectomy were observed in the late-experience group.

Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.

PubMed

Yamaguchi, Tomohiro; Kinugasa, Yusuke; Shiomi, Akio; Sato, Sumito; Yamakawa, Yushi; Kagawa, Hiroyasu; Tomioka, Hiroyuki; Mori, Keita

2015-07-01

Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single institute. From December 2011 to August 2013, a total of 80 consecutive patients who underwent robotic-assisted surgery for rectal cancer performed by the same surgeon were included in this study. The learning curve was analyzed using the cumulative sum method. This method was used for all 80 cases, taking into account operative time. Operative procedures included anterior resections in 6 patients, low anterior resections in 46 patients, intersphincteric resections in 22 patients, and abdominoperineal resections in 6 patients. Lateral lymph node dissection was performed in 28 patients. Median operative time was 280 min (range 135-683 min), and median blood loss was 17 mL (range 0-690 mL). No postoperative complications of Clavien-Dindo classification Grade III or IV were encountered. We arranged operative times and calculated cumulative sum values, allowing differentiation of three phases: phase I, Cases 1-25; phase II, Cases 26-50; and phase III, Cases 51-80. Our data suggested three phases of the learning curve in robotic-assisted surgery for rectal cancer. The first 25 cases formed the learning phase.

Facilitating students' application of the integral and the area under the curve concepts in physics problems

NASA Astrophysics Data System (ADS)

Nguyen, Dong-Hai

This research project investigates the difficulties students encounter when solving physics problems involving the integral and the area under the curve concepts and the strategies to facilitate students learning to solve those types of problems. The research contexts of this project are calculus-based physics courses covering mechanics and electromagnetism. In phase I of the project, individual teaching/learning interviews were conducted with 20 students in mechanics and 15 students from the same cohort in electromagnetism. The students were asked to solve problems on several topics of mechanics and electromagnetism. These problems involved calculating physical quantities (e.g. velocity, acceleration, work, electric field, electric resistance, electric current) by integrating or finding the area under the curve of functions of related quantities (e.g. position, velocity, force, charge density, resistivity, current density). Verbal hints were provided when students made an error or were unable to proceed. A total number of 140 one-hour interviews were conducted in this phase, which provided insights into students' difficulties when solving the problems involving the integral and the area under the curve concepts and the hints to help students overcome those difficulties. In phase II of the project, tutorials were created to facilitate students' learning to solve physics problems involving the integral and the area under the curve concepts. Each tutorial consisted of a set of exercises and a protocol that incorporated the helpful hints to target the difficulties that students expressed in phase I of the project. Focus group learning interviews were conducted to test the effectiveness of the tutorials in comparison with standard learning materials (i.e. textbook problems and solutions). Overall results indicated that students learning with our tutorials outperformed students learning with standard materials in applying the integral and the area under the curve concepts to physics problems. The results of this project provide broader and deeper insights into students' problem solving with the integral and the area under the curve concepts and suggest strategies to facilitate students' learning to apply these concepts to physics problems. This study also has significant implications for further research, curriculum development and instruction.

Learning neuroendoscopy with an exoscope system (video telescopic operating monitor): Early clinical results.

PubMed

Parihar, Vijay; Yadav, Y R; Kher, Yatin; Ratre, Shailendra; Sethi, Ashish; Sharma, Dhananjaya

2016-01-01

Steep learning curve is found initially in pure endoscopic procedures. Video telescopic operating monitor (VITOM) is an advance in rigid-lens telescope systems provides an alternative method for learning basics of neuroendoscopy with the help of the familiar principle of microneurosurgery. The aim was to evaluate the clinical utility of VITOM as a learning tool for neuroendoscopy. Video telescopic operating monitor was used 39 cranial and spinal procedures and its utility as a tool for minimally invasive neurosurgery and neuroendoscopy for initial learning curve was studied. Video telescopic operating monitor was used in 25 cranial and 14 spinal procedures. Image quality is comparable to endoscope and microscope. Surgeons comfort improved with VITOM. Frequent repositioning of scope holder and lack of stereopsis is initial limiting factor was compensated for with repeated procedures. Video telescopic operating monitor is found useful to reduce initial learning curve of neuroendoscopy.

An Exploratory Analysis of Personality, Attitudes, and Study Skills on the Learning Curve within a Team-based Learning Environment

PubMed Central

Henry, Teague; Campbell, Ashley

2015-01-01

Objective. To examine factors that determine the interindividual variability of learning within a team-based learning environment. Methods. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students’ Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. Results. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. Conclusion. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course. PMID:25861101

An exploratory analysis of personality, attitudes, and study skills on the learning curve within a team-based learning environment.

PubMed

Persky, Adam M; Henry, Teague; Campbell, Ashley

2015-03-25

To examine factors that determine the interindividual variability of learning within a team-based learning environment. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

ACQUA: Automated Cyanobacterial Quantification Algorithm for toxic filamentous genera using spline curves, pattern recognition and machine learning.

PubMed

Gandola, Emanuele; Antonioli, Manuela; Traficante, Alessio; Franceschini, Simone; Scardi, Michele; Congestri, Roberta

2016-05-01

Toxigenic cyanobacteria are one of the main health risks associated with water resources worldwide, as their toxins can affect humans and fauna exposed via drinking water, aquaculture and recreation. Microscopy monitoring of cyanobacteria in water bodies and massive growth systems is a routine operation for cell abundance and growth estimation. Here we present ACQUA (Automated Cyanobacterial Quantification Algorithm), a new fully automated image analysis method designed for filamentous genera in Bright field microscopy. A pre-processing algorithm has been developed to highlight filaments of interest from background signals due to other phytoplankton and dust. A spline-fitting algorithm has been designed to recombine interrupted and crossing filaments in order to perform accurate morphometric analysis and to extract the surface pattern information of highlighted objects. In addition, 17 specific pattern indicators have been developed and used as input data for a machine-learning algorithm dedicated to the recognition between five widespread toxic or potentially toxic filamentous genera in freshwater: Aphanizomenon, Cylindrospermopsis, Dolichospermum, Limnothrix and Planktothrix. The method was validated using freshwater samples from three Italian volcanic lakes comparing automated vs. manual results. ACQUA proved to be a fast and accurate tool to rapidly assess freshwater quality and to characterize cyanobacterial assemblages in aquatic environments. Copyright © 2016 Elsevier B.V. All rights reserved.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study.

PubMed

Dawes, Timothy J W; de Marvao, Antonio; Shi, Wenzhe; Fletcher, Tristan; Watson, Geoffrey M J; Wharton, John; Rhodes, Christopher J; Howard, Luke S G E; Gibbs, J Simon R; Rueckert, Daniel; Cook, Stuart A; Wilkins, Martin R; O'Regan, Declan P

2017-05-01

Purpose To determine if patient survival and mechanisms of right ventricular failure in pulmonary hypertension could be predicted by using supervised machine learning of three-dimensional patterns of systolic cardiac motion. Materials and Methods The study was approved by a research ethics committee, and participants gave written informed consent. Two hundred fifty-six patients (143 women; mean age ± standard deviation, 63 years ± 17) with newly diagnosed pulmonary hypertension underwent cardiac magnetic resonance (MR) imaging, right-sided heart catheterization, and 6-minute walk testing with a median follow-up of 4.0 years. Semiautomated segmentation of short-axis cine images was used to create a three-dimensional model of right ventricular motion. Supervised principal components analysis was used to identify patterns of systolic motion that were most strongly predictive of survival. Survival prediction was assessed by using difference in median survival time and area under the curve with time-dependent receiver operating characteristic analysis for 1-year survival. Results At the end of follow-up, 36% of patients (93 of 256) died, and one underwent lung transplantation. Poor outcome was predicted by a loss of effective contraction in the septum and free wall, coupled with reduced basal longitudinal motion. When added to conventional imaging and hemodynamic, functional, and clinical markers, three-dimensional cardiac motion improved survival prediction (area under the receiver operating characteristic curve, 0.73 vs 0.60, respectively; P < .001) and provided greater differentiation according to difference in median survival time between high- and low-risk groups (13.8 vs 10.7 years, respectively; P < .001). Conclusion A machine-learning survival model that uses three-dimensional cardiac motion predicts outcome independent of conventional risk factors in patients with newly diagnosed pulmonary hypertension. Online supplemental material is available for this article.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

PubMed Central

Akbari, Hamed; Macyszyn, Luke; Da, Xiao; Bilello, Michel; Wolf, Ronald L.; Martinez-Lage, Maria; Biros, George; Alonso-Basanta, Michelle; O’Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background Glioblastoma is an aggressive and highly infiltrative brain cancer. Standard surgical resection is guided by enhancement on postcontrast T1-weighted (T1) magnetic resonance imaging (MRI), which is insufficient for delineating surrounding infiltrating tumor. Objective To develop imaging biomarkers that delineate areas of tumor infiltration and predict early recurrence in peritumoral tissue. Such markers would enable intensive, yet targeted, surgery and radiotherapy, thereby potentially delaying recurrence and prolonging survival. Methods Preoperative multiparametric MRIs (T1, T1-Gad, T2-weighted [T2], T2-fluid-attenuated inversion recovery [FLAIR], diffusion tensor imaging (DTI), and dynamic susceptibility contrast-enhanced [DSC]-MRI) from 31 patients were combined using machine learning methods, thereby creating predictive spatial maps of infiltrated peritumoral tissue. Cross validation was used in the retrospective cohort to achieve generalizable biomarkers. Subsequently, the imaging signatures learned from the retrospective study were used in a replication cohort of 34 new patients. Spatial maps representing likelihood of tumor infiltration and future early recurrence were compared to regions of recurrence on postresection follow-up studies with pathology confirmation. Results This technique produced predictions of early recurrence with a mean area under the curve (AUC) of 0.84, sensitivity of 91%, specificity of 93%, and odds ratio estimates of 9.29 (99% CI, 8.95–9.65) for tissue predicted to be heavily infiltrated in the replication study. Regions of tumor recurrence were found to have subtle, yet fairly distinctive multiparametric imaging signatures when analyzed quantitatively by pattern analysis and machine learning. Conclusion Visually imperceptible imaging patterns discovered via multiparametric pattern analysis methods were found to estimate the extent of infiltration and location of future tumor recurrence, paving the way for improved targeted treatment. PMID:26813856

Activated partial thromboplastin time derivative curves: helpful diagnostic tool in mixing test interpretation.

PubMed

Esmedere Eren, Sevim; Karakukcu, Cigdem; Ciraci, Mehmet Z; Ustundag, Yasemin; Karakukcu, Musa

2018-06-01

: The mixing test is used to evaluate whether prolonged activated partial thromboplastin time (APTT) is due to an inhibitor or a factor deficiency. The coagulation reaction is demonstrated with APTT derivative curves on the ACL TOP series. We aimed to determine the utility of APTT derivative curves in the mixing test process. The plasma of a patient was mixed with normal plasma in a 1 : 1 ratio and APTT assay was performed with SynthASil reagent. We observed roughness, biphasic and shoulder patterns in derivative curves during the mixing test. An extended laboratory investigation revealed a positive lupus anticoagulant, low factors XI and IX activities. Along with mixing test cut-off limits, we recommend analysing changes in APTT derivative curves to minimize erroneous interpretations of the mixing test. Derivative curves display either a normalizing pattern in factor deficiencies or an atypical pattern in the presence of lupus anticoagulant.

Review Article: A comparison of flood and earthquake vulnerability assessment indicators

NASA Astrophysics Data System (ADS)

de Ruiter, Marleen C.; Ward, Philip J.; Daniell, James E.; Aerts, Jeroen C. J. H.

2017-07-01

In a cross-disciplinary study, we carried out an extensive literature review to increase understanding of vulnerability indicators used in the disciplines of earthquake- and flood vulnerability assessments. We provide insights into potential improvements in both fields by identifying and comparing quantitative vulnerability indicators grouped into physical and social categories. Next, a selection of index- and curve-based vulnerability models that use these indicators are described, comparing several characteristics such as temporal and spatial aspects. Earthquake vulnerability methods traditionally have a strong focus on object-based physical attributes used in vulnerability curve-based models, while flood vulnerability studies focus more on indicators applied to aggregated land-use classes in curve-based models. In assessing the differences and similarities between indicators used in earthquake and flood vulnerability models, we only include models that separately assess either of the two hazard types. Flood vulnerability studies could be improved using approaches from earthquake studies, such as developing object-based physical vulnerability curve assessments and incorporating time-of-the-day-based building occupation patterns. Likewise, earthquake assessments could learn from flood studies by refining their selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies for exploring risk assessment methodologies across different hazard types.

Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Sarah J.; Wei, Max; Sohn, Michael D.

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes inmore » the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.« less

The learning curve: Implications of a quantitative analysis

PubMed Central

Gallistel, Charles R.; Fairhurst, Stephen; Balsam, Peter

2004-01-01

The negatively accelerated, gradually increasing learning curve is an artifact of group averaging in several commonly used basic learning paradigms (pigeon autoshaping, delay- and trace-eye-blink conditioning in the rabbit and rat, autoshaped hopper entry in the rat, plus maze performance in the rat, and water maze performance in the mouse). The learning curves for individual subjects show an abrupt, often step-like increase from the untrained level of responding to the level seen in the well trained subject. The rise is at least as abrupt as that commonly seen in psychometric functions in stimulus detection experiments. It may indicate that the appearance of conditioned behavior is mediated by an evidence-based decision process, as in stimulus detection experiments. If the appearance of conditioned behavior is taken instead to reflect the increase in an underlying associative strength, then a negligible portion of the function relating associative strength to amount of experience is behaviorally visible. Consequently, rate of learning cannot be estimated from the group-average curve; the best measure is latency to the onset of responding, determined for each subject individually. PMID:15331782

The learning curve: implications of a quantitative analysis.

PubMed

Gallistel, Charles R; Fairhurst, Stephen; Balsam, Peter

2004-09-07

The negatively accelerated, gradually increasing learning curve is an artifact of group averaging in several commonly used basic learning paradigms (pigeon autoshaping, delay- and trace-eye-blink conditioning in the rabbit and rat, autoshaped hopper entry in the rat, plus maze performance in the rat, and water maze performance in the mouse). The learning curves for individual subjects show an abrupt, often step-like increase from the untrained level of responding to the level seen in the well trained subject. The rise is at least as abrupt as that commonly seen in psychometric functions in stimulus detection experiments. It may indicate that the appearance of conditioned behavior is mediated by an evidence-based decision process, as in stimulus detection experiments. If the appearance of conditioned behavior is taken instead to reflect the increase in an underlying associative strength, then a negligible portion of the function relating associative strength to amount of experience is behaviorally visible. Consequently, rate of learning cannot be estimated from the group-average curve; the best measure is latency to the onset of responding, determined for each subject individually.

Proceedings of the Ship Control Systems Symposium (9th) Held in Bethesda, Maryland on 10-14 September 1990. Theme: Automation in Surface Ship Control Systems, Today’s Applications and Future Trends. Volume 3

DTIC Science & Technology

1990-09-14

expectations tend to follow a set pattern as he sets out an the learning curve for the aplication of distributed processor systems, 3.149 those "new" systems...do the job more efficiently. Another example is the use of aplication software to replace the perfectly adequate Wilt-in logic involved with...combat system survivability. The probability of kill, Pk, of the combat system is shown decreasing from current firepower kill levels to that of mobility

Autoshaped head poking in the mouse: a quantitative analysis of the learning curve.

PubMed

Papachristos, Efstathios B; Gallistel, C R

2006-05-01

In autoshaping experiments, we quantified the acquisition of anticipatory head poking in individual mice, using an algorithm that finds changes in the slope of a cumulative record. In most mice, upward changes in the amount of anticipatory poking per trial were abrupt, and tended to occur at session boundaries, suggesting that the session is as significant a unit of experience as the trial. There were large individual differences in the latency to the onset of vigorous responding. "Asymptotic" performance was unstable; large, bidirectional, and relatively enduring changes were common. Given the characteristics of the individual learning curves, it is unlikely that physiologically meaningful estimates of rate of learning can be extracted from group-average learning curves.

Autoshaped Head Poking in the Mouse: A Quantitative Analysis of the Learning Curve

PubMed Central

Papachristos, Efstathios B; Gallistel, C.R

2006-01-01

In autoshaping experiments, we quantified the acquisition of anticipatory head poking in individual mice, using an algorithm that finds changes in the slope of a cumulative record. In most mice, upward changes in the amount of anticipatory poking per trial were abrupt, and tended to occur at session boundaries, suggesting that the session is as significant a unit of experience as the trial. There were large individual differences in the latency to the onset of vigorous responding. “Asymptotic” performance was unstable; large, bidirectional, and relatively enduring changes were common. Given the characteristics of the individual learning curves, it is unlikely that physiologically meaningful estimates of rate of learning can be extracted from group-average learning curves. PMID:16776053

Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.

Variation in learning curves and competence for ERCP among advanced endoscopy trainees by using cumulative sum analysis.

PubMed

Wani, Sachin; Hall, Matthew; Wang, Andrew Y; DiMaio, Christopher J; Muthusamy, V Raman; Keswani, Rajesh N; Brauer, Brian C; Easler, Jeffrey J; Yen, Roy D; El Hajj, Ihab; Fukami, Norio; Ghassemi, Kourosh F; Gonzalez, Susana; Hosford, Lindsay; Hollander, Thomas G; Wilson, Robert; Kushnir, Vladimir M; Ahmad, Jawad; Murad, Faris; Prabhu, Anoop; Watson, Rabindra R; Strand, Daniel S; Amateau, Stuart K; Attwell, Augustin; Shah, Raj J; Early, Dayna; Edmundowicz, Steven A; Mullady, Daniel

2016-04-01

There are limited data on learning curves and competence in ERCP. By using a standardized data collection tool, we aimed to prospectively define learning curves and measure competence among advanced endoscopy trainees (AETs) by using cumulative sum (CUSUM) analysis. AETs were evaluated by attending endoscopists starting with the 26th hands-on ERCP examination and then every ERCP examination during the 12-month training period. A standardized ERCP competency assessment tool (using a 4-point scoring system) was used to grade the examination. CUSUM analysis was applied to produce learning curves for individual technical and cognitive components of ERCP performance (success defined as a score of 1, acceptable and unacceptable failures [p1] of 10% and 20%, respectively). Sensitivity analyses varying p1 and by using a less-stringent definition of success were performed. Five AETs were included with a total of 1049 graded ERCPs (mean ± SD, 209.8 ± 91.6/AET). The majority of cases were performed for a biliary indication (80%). The overall and native papilla allowed cannulation times were 3.1 ± 3.6 and 5.7 ± 4, respectively. Overall learning curves demonstrated substantial variability for individual technical and cognitive endpoints. Although nearly all AETs achieved competence in overall cannulation, none achieved competence for cannulation in cases with a native papilla. Sensitivity analyses increased the proportion of AETs who achieved competence. This study demonstrates that there is substantial variability in ERCP learning curves among AETs. A specific case volume does not ensure competence, especially for native papilla cannulation. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Robotic radical prostatectomy learning curve of a fellowship-trained laparoscopic surgeon.

PubMed

Zorn, Kevin C; Orvieto, Marcelo A; Gong, Edward M; Mikhail, Albert A; Gofrit, Ofer N; Zagaja, Gregory P; Shalhav, Arieh L

2007-04-01

Several experienced practitioners of open surgery with limited or no laparoscopic background have adopted robot-assisted laparoscopic radical prostatectomy (RLRP) as an alternative to open radical prostatectomy (RRP), demonstrating outcomes comparable to those in large RRP and laparoscopic prostatectomy series. Thus, the significance of prior laparoscopic skills seems unclear. The learning curve, with respect to operative time and complications, in the hands of a devoted laparoscopic surgeon has not been critically assessed. We evaluated the learning curve of a highly experienced laparoscopic surgeon in achieving expertise with RLRP. We prospectively evaluated 150 consecutive patients undergoing RLRP by a single surgeon between March 2003 and September 2005. The first 25 cases were performed with the assistance of a surgeon experienced in open RRP. Data were compared for the first, second, and third groups of 50 cases. Demographic data were similar for the three groups. Urinary and sexual function data were evaluated subjectively and objectively using the RAND-36v2 Survey and the UCLA PCI preoperatively and at 3, 6, and 12 months postoperatively. The mean operative time, blood loss, and conversion rate decreased significantly with increasing experience. All open conversions occurred during the first 25 cases. Intraoperative and postoperative complication rates were similar among groups. Although the differences were not significant, urinary and sexual function recovery improved with experience. The RLRP learning curve for a fellowship-trained laparoscopic surgeon seems to be similar to that of laparoscopically naive yet experienced practitioners of open RRP. The RLRP is safe and reproducible and even during the learning curve can produce results similar to those reported in large RRP series. The importance of assistance by an experienced open RRP surgeon during the learning curve cannot be overemphasized.

The learning curve in robotic distal pancreatectomy.

PubMed

Napoli, Niccolò; Kauffmann, Emanuele F; Perrone, Vittorio Grazio; Miccoli, Mario; Brozzetti, Stefania; Boggi, Ugo

2015-09-01

No data are available on the learning curve in robotic distal pancreatectomy (RADP). The learning curve in RADP was assessed in 55 consecutive patients using the cumulative sum method, based on operative time. Data were extracted from a prospectively maintained database and analyzed retrospectively considering all events occurring within 90 days of surgery. No operation was converted to laparoscopic or open surgery and no patient died. Post-operative complications occurred in 34 patients (61.8%), being of Clavien-Dindo grade I-II in 32 patients (58.1%), including pancreatic fistula in 29 patients (52.7%). No grade C pancreatic fistula occurred. Four patients received blood transfusions (7.2%), three were readmitted (5.4%) and one required repeat surgery (1.8%). Based on the reduction of operative times (421.1 ± 20.5 vs 248.9 ± 9.3 min; p < 0.0001), completion of the learning curve was achieved after ten operations. Operative time of the first 10 operations was associated with a positive slope (0.47 + 1.78* case number; R (2) 0.97; p < 0.0001*), while that of the following 45 procedures showed a negative slope (23.52 - 0.39* case number; R (2) 0.97; p < 0.0001*). After completion of the learning curve, more patients had a malignant histology (0 vs 35.6%; p = 0.002), accounting for both higher lymph node yields (11.1 ± 12.2 vs 20.9 ± 18.5) (p = 0.04) and lower rate of spleen preservation (90 vs 55.6%) (p = 0.04). RADP was safely feasible in selected patients and the learning curve was completed after ten operations. Improvement in clinical outcome was not demonstrated, probably because of the limited occurrence of outcome comparators.

Robotic partial nephrectomy - Evaluation of the impact of case mix on the procedural learning curve.

PubMed

Roman, A; Ahmed, K; Challacombe, B

2016-05-01

Although Robotic partial nephrectomy (RPN) is an emerging technique for the management of small renal masses, this approach is technically demanding. To date, there is limited data on the nature and progression of the learning curve in RPN. To analyse the impact of case mix on the RPN LC and to model the learning curve. The records of the first 100 RPN performed, were analysed at our institution that were carried out by a single surgeon (B.C) (June 2010-December 2013). Cases were split based on their Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score into the following groups: 6-7, 8-9 and >10. Using a split group (20 patients in each group) and incremental analysis, the mean, the curve of best fit and R(2) values were calculated for each group. Of 100 patients (F:28, M:72), the mean age was 56.4 ± 11.9 years. The number of patients in each PADUA score groups: 6-7, 8-9 and >10 were 61, 32 and 7 respectively. An increase in incidence of more complex cases throughout the cohort was evident within the 8-9 group (2010: 1 case, 2013: 16 cases). The learning process did not significantly affect the proxies used to assess surgical proficiency in this study (operative time and warm ischaemia time). Case difficulty is an important parameter that should be considered when evaluating procedural learning curves. There is not one well fitting model that can be used to model the learning curve. With increasing experience, clinicians tend to operate on more difficult cases. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Learning Curve and Clinical Outcomes of Performing Surgery with the InterTan Intramedullary Nail in Treating Femoral Intertrochanteric Fractures

PubMed Central

2017-01-01

Purpose. The purpose of this study is to evaluate the learning curve of performing surgery with the InterTan intramedullary nail in treating femoral intertrochanteric fractures, to provide valuable information and experience for surgeons who decide to learn a new procedure. Methods. We retrospectively analyzed data from 53 patients who underwent surgery using an InterTan intramedullary nail at our hospital between July 2012 and September 2015. The negative exponential curve-fit regression analysis was used to evaluate the learning curve. According to 90% learning milestone, patients were divided into two group, and the outcomes were compared. Results. The mean operative time was 69.28 (95% CI 64.57 to 74.00) minutes; with the accumulation of surgical experience, the operation time was gradually decreased. 90% of the potential improvement was expected after 18 cases. In terms of operative time, intraoperative blood loss, hospital stay, and Harris hip score significant differences were found between two groups (p = 0.009, p = 0.000, p = 0.030, and p = 0.002, resp.). Partial weight bearing time, fracture union time, tip apex distance, and the number of blood transfusions and complications were similar between two groups (p > 0.5). Conclusion. This study demonstrated that the learning curve of performing surgery with the InterTan intramedullary nail is acceptable and 90% of the expert's proficiency level is achieved at around 18 cases. PMID:28503572

Estimating the cost of production stoppage

NASA Technical Reports Server (NTRS)

Delionback, L. M.

1979-01-01

Estimation model considers learning curve quantities, and time of break to forecast losses due to break in production schedule. Major parameters capable of predicting costs are number of units made prior to production sequence, length of production break, and slope of learning curve produced prior to break.

Experience and learning curve of retroperitoneal laparoscopic ureterolithotomy for upper ureteral calculi.

PubMed

Fan, Tianyong; Xian, Peng; Yang, Lu; Liu, Yong; Wei, Qiang; Li, Hong

2009-11-01

To summarize our experience and evaluate the learning curve of retroperitoneal laparoscopic ureterolithotomy of the upper ureter. Between May 2004 and May 2007, 40 patients underwent retroperitoneal laparoscopic ureterolithotomy of the upper ureter. We divided the first and last 20 patients into group I and group II. There was no statistical difference in stone size between groups. Operative time and complications were measured as a basis for the assessment of the learning curve. In group I, the complication rate was 15% (3/20), including two patients whose procedure was converted to open surgery because of intraoperative bleeding, and one patient who experienced urine leakage because of a displaced Double-J ureteral stent. In group II, no postoperative complications occurred, while the mean operative time was significantly shorter compared with the earlier operations (65 vs 120 min). Retroperitoneal laparoscopic ureterolithotomy is safe and effective for large or impacted stones of the upper ureter. It is associated with a short learning curve in the setting of an active laparoscopic practice for selected patients.

[Pancreatoduodenectomy: learning curve within single multi-field center].

PubMed

Kaprin, A D; Kostin, A A; Nikiforov, P V; Egorov, V I; Grishin, N A; Lozhkin, M V; Petrov, L O; Bykasov, S A; Sidorov, D V

2018-01-01

To analyze learning curve by using of immediate results of pancreatoduodenectomy at multi-field oncology institute. For the period 2010-2016 at Abdominal Oncology Department of Herzen Moscow Oncology Research Institute 120 pancreatoduodenal resections were consistently performed. All patients were divided into two groups: the first 60 procedures (group A) and subsequent 60 operations (group B). Herewith, first 60 operations were performed within the first 4.5 years of study period, the next 60 operations - within remaining 2.5 years. Learning curves showed significantly variable intraoperative blood loss (1100 ml and 725 ml), surgery time (589 min and 513 min) and postoperative hospital-stay (15 days and 13 days) in group A followed by gradual improvement of these values in group B. Incidence of negative resection margin (R0) was also significantly improved in the last 60 operations (70 and 92%, respectively). Despite pancreatoduodenectomy is one of the most difficult surgical interventions in abdominal surgery learning curve will differ from one surgeon to another.

Effect of parental family history of Alzheimer's disease on serial position profiles.

PubMed

La Rue, Asenath; Hermann, Bruce; Jones, Jana E; Johnson, Sterling; Asthana, Sanjay; Sager, Mark A

2008-07-01

An exaggerated recency effect (ie, disproportionate recall of last-presented items) has been consistently observed in the word list learning of patients with Alzheimer's disease (AD). Our study sought to determine whether there were similar alterations in serial position learning among asymptomatic persons at risk for AD as a result of parental family history. Subjects included 623 asymptomatic middle-aged children of patients with AD (median, 53 years) and 157 control participants whose parents survived to at least age 70 without AD or other memory disorders. All participants were administered the Rey Auditory Verbal Learning Test, which requires learning and recall of 15 unrelated nouns. There was no significant difference in total words recalled between the AD children and control groups. However, compared with controls, AD children exhibited a significantly greater tendency to recall words from the end (recency) versus beginning (primacy) of the list. Serial position effects were unrelated to apolipoprotein allele epsilon 4 or depressive symptoms. Asymptomatic persons at risk for AD by virtue of family history do not show a difference in total words recalled compared with controls, but they exhibit a distinctly different serial position curve, suggesting greater reliance on immediate as opposed to episodic memory. This is the same serial position pattern observed in mild AD, seen here in reduced severity. Longitudinal follow-up is planned to determine whether changes in serial position patterns are a meaningful marker for preclinical detection of AD.

Robotic thyroidectomy learning curve for beginning surgeons with little or no experience of endoscopic surgery.

PubMed

Park, Jae Hyun; Lee, Jandee; Hakim, Nor Azham; Kim, Ha Yan; Kang, Sang-Wook; Jeong, Jong Ju; Nam, Kee-Hyun; Bae, Keum-Seok; Kang, Seong Joon; Chung, Woong Youn

2015-12-01

This study assessed the results of robotic thyroidectomy by fellowship-trained surgeons in their initial independent practice, and whether standard fellowship training for robotic surgery shortens the learning curve. This prospective cohort study evaluated outcomes in 125 patients who underwent robotic thyroidectomy using gasless transaxillary single-incision technique by 2 recently graduated fellowship-trained surgeons. Learning curves were analyzed by operation time, with proficiency defined as the point at which the slope of the time curve became less steep. Of the 125 patients, 113 underwent robotic less-than-total thyroidectomy, 9 underwent robotic total thyroidectomy and 3 underwent robotic total thyroidectomy with modified radical neck dissection. Mean total times for these 3 operations were 100.8 ± 20.6 minutes, 134.2 ± 38.7 minutes, and 284.7 ± 60.4 minutes, respectively. For both surgeons, the operation times gradually decreased, reaching a plateau after 20 robotic less-than-total thyroidectomies. The surgical learning curve for robotic thyroidectomy performed by recently graduated fellowship-trained surgeons with little or no experience in endoscopic surgery showed excellent results compared with those in a large series of more experienced surgeons. © 2014 Wiley Periodicals, Inc.

Annual variation in the atmospheric radon concentration in Japan.

PubMed

Kobayashi, Yuka; Yasuoka, Yumi; Omori, Yasutaka; Nagahama, Hiroyuki; Sanada, Tetsuya; Muto, Jun; Suzuki, Toshiyuki; Homma, Yoshimi; Ihara, Hayato; Kubota, Kazuhito; Mukai, Takahiro

2015-08-01

Anomalous atmospheric variations in radon related to earthquakes have been observed in hourly exhaust-monitoring data from radioisotope institutes in Japan. The extraction of seismic anomalous radon variations would be greatly aided by understanding the normal pattern of variation in radon concentrations. Using atmospheric daily minimum radon concentration data from five sampling sites, we show that a sinusoidal regression curve can be fitted to the data. In addition, we identify areas where the atmospheric radon variation is significantly affected by the variation in atmospheric turbulence and the onshore-offshore pattern of Asian monsoons. Furthermore, by comparing the sinusoidal regression curve for the normal annual (seasonal) variations at the five sites to the sinusoidal regression curve for a previously published dataset of radon values at the five Japanese prefectures, we can estimate the normal annual variation pattern. By fitting sinusoidal regression curves to the previously published dataset containing sites in all Japanese prefectures, we find that 72% of the Japanese prefectures satisfy the requirements of the sinusoidal regression curve pattern. Using the normal annual variation pattern of atmospheric daily minimum radon concentration data, these prefectures are suitable areas for obtaining anomalous radon variations related to earthquakes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using learning curves on energy-efficient technologies to estimate future energy savings and emission reduction potentials in the U.S. iron and steel industry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Park, Won Young; McNeil, Michael A.

Increasing concerns on non-sustainable energy use and climate change spur a growing research interest in energy efficiency potentials in various critical areas such as industrial production. This paper focuses on learning curve aspects of energy efficiency measures in the U.S iron and steel sector. A number of early-stage efficient technologies (i.e., emerging or demonstration technologies) are technically feasible and have the potential to make a significant contribution to energy saving and CO 2 emissions reduction, but fall short economically to be included. However, they may also have the cost effective potential for significant cost reduction and/or performance improvement in themore » future under learning effects such as ‘learning-by-doing’. The investigation is carried out using ISEEM, a technology oriented, linear optimization model. We investigated how steel demand is balanced with/without the availability learning curve, compared to a Reference scenario. The retrofit (or investment in some cases) costs of energy efficient technologies decline in the scenario where learning curve is applied. The analysis also addresses market penetration of energy efficient technologies, energy saving, and CO 2 emissions in the U.S. iron and steel sector with/without learning impact. Accordingly, the study helps those who use energy models better manage the price barriers preventing unrealistic diffusion of energy-efficiency technologies, better understand the market and learning system involved, predict future achievable learning rates more accurately, and project future savings via energy-efficiency technologies with presence of learning. We conclude from our analysis that, most of the existing energy efficiency technologies that are currently used in the U.S. iron and steel sector are cost effective. Penetration levels increases through the years, even though there is no price reduction. However, demonstration technologies are not economically feasible in the U.S. iron and steel sector with the current cost structure. In contrast, some of the demonstration technologies are adapted in the mid-term and their penetration levels increase as the prices go down with learning curve. We also observe large penetration of 225kg pulverized coal injection with the presence of learning.« less

Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

2017-02-01

We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

Early experience in microtia reconstruction: the first 100 cases.

PubMed

Sabbagh, Walid

2011-04-01

Auricular reconstruction in Microtia is a challenging operation with a steep learning curve. In view its rarity attaining a high standard for new surgeons is extremely difficult. This study analyses the first 100 microtia cases looking at complications, technique, pattern of progress and aesthetic outcome. The author performed 100 autologous ear reconstructions for microtia over a period of 4 years utilizing the two stage technique popularised by Nagata and Firmin. In 11 cases a temroparietal fascial flap was utilised because of either a low hairline or scarring. Follow up ranged from 3 to 36 months. Data was collected prospectively. There were 7 cases of partial skin necrosis, 3 of which healed with conservative management. In early cases deficiencies were seen in the proportions of the reconstructed ear and the quality of definition. Better shape and definition were evident as more surgical experience was gained. This occurred as a result of increased appreciation of the ear proportions and improved framework carving. Although two stages were planned 21 cases required further procedures. The series demonstrates the early learning curve in microtia reconstruction and underlines the importance of appropriate training and case availability in achieving high quality results in autologous ear reconstruction. Copyright © 2010 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Microvascular Anastomosis: Proposition of a Learning Curve.

PubMed

Mokhtari, Pooneh; Tayebi Meybodi, Ali; Benet, Arnau; Lawton, Michael T

2018-04-14

Learning to perform a microvascular anastomosis is one of the most difficult tasks in cerebrovascular surgery. Previous studies offer little regarding the optimal protocols to maximize learning efficiency. This failure stems mainly from lack of knowledge about the learning curve of this task. To delineate this learning curve and provide information about its various features including acquisition, improvement, consistency, stability, and recall. Five neurosurgeons with an average surgical experience history of 5 yr and without any experience in bypass surgery performed microscopic anastomosis on progressively smaller-caliber silastic tubes (Biomet, Palm Beach Gardens, Florida) during 24 consecutive sessions. After a 1-, 2-, and 8-wk retention interval, they performed recall test on 0.7-mm silastic tubes. The anastomoses were rated based on anastomosis patency and presence of any leaks. Improvement rate was faster during initial sessions compared to the final practice sessions. Performance decline was observed in the first session of working on a smaller-caliber tube. However, this rapidly improved during the following sessions of practice. Temporary plateaus were seen in certain segments of the curve. The retention interval between the acquisition and recall phase did not cause a regression to the prepractice performance level. Learning the fine motor task of microvascular anastomosis adapts to the basic rules of learning such as the "power law of practice." Our results also support the improvement of performance during consecutive sessions of practice. The objective evidence provided may help in developing optimized learning protocols for microvascular anastomosis.

Training, Simulation, the Learning Curve, and How to Reduce Complications in Urology.

PubMed

Brunckhorst, Oliver; Volpe, Alessandro; van der Poel, Henk; Mottrie, Alexander; Ahmed, Kamran

2016-04-01

Urology is at the forefront of minimally invasive surgery to a great extent. These procedures produce additional learning challenges and possess a steep initial learning curve. Training and assessment methods in surgical specialties such as urology are known to lack clear structure and often rely on differing operative flow experienced by individuals and institutions. This article aims to assess current urology training modalities, to identify the role of simulation within urology, to define and identify the learning curves for various urologic procedures, and to discuss ways to decrease complications in the context of training. A narrative review of the literature was conducted through December 2015 using the PubMed/Medline, Embase, and Cochrane Library databases. Evidence of the validity of training methods in urology includes observation of a procedure, mentorship and fellowship, e-learning, and simulation-based training. Learning curves for various urologic procedures have been recommended based on the available literature. The importance of structured training pathways is highlighted, with integration of modular training to ensure patient safety. Valid training pathways are available in urology. The aim in urology training should be to combine all of the available evidence to produce procedure-specific curricula that utilise the vast array of training methods available to ensure that we continue to improve patient outcomes and reduce complications. The current evidence for different training methods available in urology, including simulation-based training, was reviewed, and the learning curves for various urologic procedures were critically analysed. Based on the evidence, future pathways for urology curricula have been suggested to ensure that patient safety is improved. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

The 1974 AVCR Young Scholar Paper: An Open-System Model of Learning

ERIC Educational Resources Information Center

Winn, William

1975-01-01

Rejecting the cybernetic model of the learner, the author offers an open-system model based on von Bertalanffy's equation for growth of the living organism. The model produces four learning curves, not just the logarithmic curve produced by the successive approximations of the cybernetic model. (Editor)

A learning curve for solar thermal power

NASA Astrophysics Data System (ADS)

Platzer, Werner J.; Dinter, Frank

2016-05-01

Photovoltaics started its success story by predicting the cost degression depending on cumulated installed capacity. This so-called learning curve was published and used for predictions for PV modules first, then predictions of system cost decrease also were developed. This approach is less sensitive to political decisions and changing market situations than predictions on the time axis. Cost degression due to innovation, use of scaling effects, improved project management, standardised procedures including the search for better sites and optimization of project size are learning effects which can only be utilised when projects are developed. Therefore a presentation of CAPEX versus cumulated installed capacity is proposed in order to show the possible future advancement of the technology to politics and market. However from a wide range of publications on cost for CSP it is difficult to derive a learning curve. A logical cost structure for direct and indirect capital expenditure is needed as the basis for further analysis. Using derived reference cost for typical power plant configurations predictions of future cost have been derived. Only on the basis of that cost structure and the learning curve levelised cost of electricity for solar thermal power plants should be calculated for individual projects with different capacity factors in various locations.

Generalized elastica patterns in a curved rotating Hele-Shaw cell

NASA Astrophysics Data System (ADS)

Brandão, Rodolfo; Miranda, José A.

2017-08-01

We study a family of generalized elasticalike equilibrium shapes that arise at the interface separating two fluids in a curved rotating Hele-Shaw cell. This family of stationary interface solutions consists of shapes that balance the competing capillary and centrifugal forces in such a curved flow environment. We investigate how the emerging interfacial patterns are impacted by changes in the geometric properties of the curved Hele-Shaw cell. A vortex-sheet formalism is used to calculate the two-fluid interface curvature, and a gallery of possible shapes is provided to highlight a number of peculiar morphological features. A linear perturbation theory is employed to show that the most prominent aspects of these complex stationary patterns can be fairly well reproduced by the interplay of just two interfacial modes. The connection of these dominant modes to the geometry of the curved cell, as well as to the fluid dynamic properties of the flow, is discussed.

Cumulative sum analysis for experiences of a single-session retrograde intrarenal stone surgery and analysis of predictors for stone-free status.

PubMed

Cho, Sung Yong; Choo, Min Soo; Jung, Jae Hyun; Jeong, Chang Wook; Oh, Sohee; Lee, Seung Bae; Son, Hwancheol; Jeong, Hyeon

2014-01-01

This study investigated the learning curve of a single-session retrograde intrarenal surgery (RIRS) in patients with mid-sized stones. Competence and trainee proficiency for RIRS was assessed using cumulative sum analysis (CUSUM). The study design and the use of patients' information stored in the hospital database were approved by the Institutional Review Board of our institution. A retrospective review was performed for 100 patients who underwent a single-session RIRS. Patients were included if the main stone had a maximal diameter between 10 and 30 mm. The presence of a residual stone was checked on postoperative day 1 and at one-month follow-up visit. Fragmentation efficacy was calculated "removed stone volume (mm(3)) divided by operative time (min)". CUSUM analysis was used for monitoring change in fragmentation efficacy, and we tested whether or not acceptable surgical outcomes were achieved. The mean age was 54.7±14.8 years. Serum creatinine level did not change significantly. Estimated GFR and hemoglobin were within normal limits postoperatively. The CUSUM curve tended to be flat until the 25th case and showed a rising pattern but declined again until the 56th case. After that point, the fragmentation efficacy reached a plateau. The acceptable level of fragmentation efficacy was 25 ml/min. Multivariate logistic regression analyses showed that stone-free rate was significantly lower for cases with multiple stones than those with a single stone (OR = 0.147, CI 0.032 - 0.674, P value  = 0.005) and for cases with higher number of sites (OR = 0.676, CI 0.517 - 0.882, P value  = 0.004). The statistical analysis of RIRS learning experience revealed that 56 cases were required for reaching a plateau in the learning curve. The number of stones and the number of sites were significant predictors for stone-free status.

Spontaneous regression of curve in immature idiopathic scoliosis - does spinal column play a role to balance? An observation with literature review.

PubMed

Modi, Hitesh N; Suh, Seung-Woo; Yang, Jae-Hyuk; Hong, Jae-Young; Venkatesh, Kp; Muzaffar, Nasir

2010-11-04

Child with mild scoliosis is always a subject of interest for most orthopaedic surgeons regarding progression. Literature described Hueter-Volkmann theory regarding disc and vertebral wedging, and muscular imbalance for the progression of adolescent idiopathic scoliosis. However, many authors reported spontaneous resolution of curves also without any reason for that and the rate of resolution reported is almost 25%. Purpose of this study was to question the role of paraspinal muscle tuning/balancing mechanism, especially in patients with idiopathic scoliosis with early mild curve, for spontaneous regression or progression as well as changing pattern of curves. An observational study of serial radiograms in 169 idiopathic scoliosis children (with minimum follow-up one year) was carried. All children with Cobb angle < 25° and who were diagnosed for the first time were selected. As a sign of immaturity at the time of diagnosis, all children had Risser sign 0. No treatment was given to entire study group. Children were divided in three groups at final follow-up: Group A, B and C as children with regression, no change and progression of their curves, respectively. Additionally changes in the pattern of curve were also noted. Average age was 9.2 years at first visit and 10.11 years at final follow-up with an average follow-up of 21 months. 32.5% (55/169), 41.4% (70/169) and 26% (44/169) children exhibited regression, no change and progression in their curves, respectively. 46.1% of children (78/169) showed changing pattern of their curves during the follow-up visits before it settled down to final curve. Comparing final fate of curve with side of curve and number of curves it did not show any relationship (p > 0.05) in our study population. Possible reason for changing patterns could be better explained by the tuning/balancing mechanism of spinal column that makes an effort to balance the spine and result into spontaneous regression or prevent further progression of curve. If this which we called as "tuning/balancing mechanism" fails, curve will ultimately progress.

Statistical assessment of the learning curves of health technologies.

PubMed

Ramsay, C R; Grant, A M; Wallace, S A; Garthwaite, P H; Monk, A F; Russell, I T

2001-01-01

(1) To describe systematically studies that directly assessed the learning curve effect of health technologies. (2) Systematically to identify 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. (3) To test these statistical techniques in data sets from studies of varying designs to assess health technologies in which learning curve effects are known to exist. METHODS - STUDY SELECTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): For a study to be included, it had to include a formal analysis of the learning curve of a health technology using a graphical, tabular or statistical technique. METHODS - STUDY SELECTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): For a study to be included, it had to include a formal assessment of a learning curve using a statistical technique that had not been identified in the previous search. METHODS - DATA SOURCES: Six clinical and 16 non-clinical biomedical databases were searched. A limited amount of handsearching and scanning of reference lists was also undertaken. METHODS - DATA EXTRACTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): A number of study characteristics were abstracted from the papers such as study design, study size, number of operators and the statistical method used. METHODS - DATA EXTRACTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): The new statistical techniques identified were categorised into four subgroups of increasing complexity: exploratory data analysis; simple series data analysis; complex data structure analysis, generic techniques. METHODS - TESTING OF STATISTICAL METHODS: Some of the statistical methods identified in the systematic searches for single (simple) operator series data and for multiple (complex) operator series data were illustrated and explored using three data sets. The first was a case series of 190 consecutive laparoscopic fundoplication procedures performed by a single surgeon; the second was a case series of consecutive laparoscopic cholecystectomy procedures performed by ten surgeons; the third was randomised trial data derived from the laparoscopic procedure arm of a multicentre trial of groin hernia repair, supplemented by data from non-randomised operations performed during the trial. RESULTS - HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW: Of 4571 abstracts identified, 272 (6%) were later included in the study after review of the full paper. Some 51% of studies assessed a surgical minimal access technique and 95% were case series. The statistical method used most often (60%) was splitting the data into consecutive parts (such as halves or thirds), with only 14% attempting a more formal statistical analysis. The reporting of the studies was poor, with 31% giving no details of data collection methods. RESULTS - NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH: Of 9431 abstracts assessed, 115 (1%) were deemed appropriate for further investigation and, of these, 18 were included in the study. All of the methods for complex data sets were identified in the non-clinical literature. These were discriminant analysis, two-stage estimation of learning rates, generalised estimating equations, multilevel models, latent curve models, time series models and stochastic parameter models. In addition, eight new shapes of learning curves were identified. RESULTS - TESTING OF STATISTICAL METHODS: No one particular shape of learning curve performed significantly better than another. The performance of 'operation time' as a proxy for learning differed between the three procedures. Multilevel modelling using the laparoscopic cholecystectomy data demonstrated and measured surgeon-specific and confounding effects. The inclusion of non-randomised cases, despite the possible limitations of the method, enhanced the interpretation of learning effects. CONCLUSIONS - HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW: The statistical methods used for assessing learning effects in health technology assessment have been crude and the reporting of studies poor. CONCLUSIONS - NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH: A number of statistical methods for assessing learning effects were identified that had not hitherto been used in health technology assessment. There was a hierarchy of methods for the identification and measurement of learning, and the more sophisticated methods for both have had little if any use in health technology assessment. This demonstrated the value of considering fields outside clinical research when addressing methodological issues in health technology assessment. CONCLUSIONS - TESTING OF STATISTICAL METHODS: It has been demonstrated that the portfolio of techniques identified can enhance investigations of learning curve effects. (ABSTRACT TRUNCATED)

Huang's three-step maneuver shortens the learning curve of laparoscopic spleen-preserving splenic hilar lymphadenectomy.

PubMed

Huang, Chang-Ming; Huang, Ze-Ning; Zheng, Chao-Hui; Li, Ping; Xie, Jian-Wei; Wang, Jia-Bin; Lin, Jian-Xian; Jun, Lu; Chen, Qi-Yue; Cao, Long-Long; Lin, Mi; Tu, Ru-Hong

2017-12-01

The goal of this study was to investigate the difference between the learning curves of different maneuvers in laparoscopic spleen-preserving splenic hilar lymphadenectomy for advanced upper gastric cancer. From January 2010 to April 2014, 53 consecutive patients who underwent laparoscopic spleen-preserving splenic hilar lymphadenectomy via the traditional-step maneuver (group A) and 53 consecutive patients via Huang's three-step maneuver (group B) were retrospectively analyzed. No significant difference in patient characteristics were found between the two groups. The learning curves of groups A and B were divided into phase 1 (1-43 cases and 1-30 cases, respectively) and phase 2 (44-53 cases and 31-53 cases, respectively). Compared with group A, the dissection time, bleeding loss and vascular injury were significantly decreased in group B. No significant differences in short-term outcomes were found between the two maneuvers. The multivariate analysis indicated that the body mass index, short gastric vessels, splenic artery type and maneuver were significantly associated with the dissection time in group B. No significant difference in the survival curve was found between the maneuvers. The learning curve of Huang's three-step maneuver was shorter than that of the traditional-step maneuver, and the former represents an ideal maneuver for laparoscopic spleen-preserving splenic hilar lymphadenectomy.To shorten the learning curve at the beginning of laparoscopic spleen-preserving splenic hilar lymphadenectomy, beginners should beneficially use Huang's three-step maneuver and select patients with advanced upper gastric cancer with a body mass index of less than 25 kg/m 2 and the concentrated type of splenic artery. Copyright © 2017. Published by Elsevier Ltd.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum.

PubMed

Olde Scheper, Tjeerd V; Meredith, Rhiannon M; Mansvelder, Huibert D; van Pelt, Jaap; van Ooyen, Arjen

2017-01-01

Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.

Urgent and Elective Robotic Single-Site Cholecystectomy: Analysis and Learning Curve of 150 Consecutive Cases.

PubMed

Kubat, Eric; Hansen, Nathan; Nguyen, Huy; Wren, Sherry M; Eisenberg, Dan

2016-03-01

The use of robotic single-site cholecystectomy has increased exponentially. There are few reports describing the safety, efficacy, and operative learning curve of robotic single-site cholecystectomy either in the community setting or with nonelective surgery. We performed a retrospective review of a prospective database of our initial experience with robotic single-site cholecystectomy. Demographics and perioperative outcomes were evaluated for both urgent and elective cholecystectomy. Cumulative sum analysis was performed to determine the surgeon's learning curve. One hundred fifty patients underwent robotic single-site cholecystectomy. Seventy-four (49.3%) patients underwent urgent robotic single-site cholecystectomy, and 76 (50.7%) underwent elective robotic single-site cholecystectomy. Mean total operative time for robotic single-site cholecystectomy was 83.3 ± 2.7 minutes. Mean operative time for the urgent cohort was significantly longer than for the elective cohort (95.0 ± 4.4 versus 71.9 ± 2.6 minutes; P < .001). There was one conversion in the urgent cohort and none in the elective cohort. There was one bile duct injury (0.7%) in the urgent cohort. Perioperative complications occurred in 8.7% of patients, and most consisted of superficial surgical-site infections. There were no incisional hernias detected. The surgeon's learning curve, inclusive of urgent and elective cases, was 48 operations. Robotic single-site cholecystectomy can be performed safely and effectively in both elective and urgent cholecystectomy with a reasonable learning curve and acceptable perioperative outcomes.

Evaluation of the learning curve for external cephalic version using cumulative sum analysis.

PubMed

Kim, So Yun; Han, Jung Yeol; Chang, Eun Hye; Kwak, Dong Wook; Ahn, Hyun Kyung; Ryu, Hyun Mi; Kim, Moon Young

2017-07-01

We evaluated the learning curve for external cephalic version (ECV) using learning curve-cumulative sum (LC-CUSUM) analysis. This was a retrospective study involving 290 consecutive cases between October 2013 and March 2017. We evaluated the learning curve for ECV on nulli and over para 1 group using LC-CUSUM analysis on the assumption that 50% and 70% of ECV procedures succeeded by description a trend-line of quadratic function with reliable R 2 values. The overall success rate for ECV was 64.8% (188/290), while the success rate for nullipara and over para 1 groups was 56.2% (100/178) and 78.6% (88/112), respectively. 'H' value, that the actual failure rate does not differ from the acceptable failure rate, was -3.27 and -1.635 when considering ECV success rates of 50% and 70%, respectively. Consequently, in order to obtain a consistent 50% success rate, we would require 57 nullipara cases, and in order to obtain a consistent 70% success rate, we would require 130 nullipara cases. In contrast, 8 to 10 over para 1 cases would be required for an expected success rate of 50% and 70% on over para 1 group. Even a relatively inexperienced physician can experience success with multipara and after accumulating experience, they will manage nullipara cases. Further research is required for LC-CUSUM involving several practitioners instead of a single practitioner. This will lead to the gradual implementation of standard learning curve guidelines for ECV.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PubMed

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

The learning curves in living donor hemiliver graft procurement using small upper midline incision.

PubMed

Ikegami, Toru; Harimoto, Norifumi; Shimokawa, Masahiro; Yoshizumi, Tomoharu; Uchiyama, Hideaki; Itoh, Shinji; Okabe, Norihisa; Sakata, Kazuhito; Nagatsu, Akihisa; Soejima, Yuji; Maehara, Yoshihiko

2016-12-01

The learning curve for performing living donor hemiliver procurement (LDHP) via small upper midline incision (UMI) has not been determined. Living donors (n=101) who underwent LDHP via UMI were included to investigate the learning curve using cumulative sum analysis. The cumulative sum analysis showed that nine cases for right lobe (case #23) and 19 cases for left lobe (case #32 in the whole series) are needed for stable and acceptable surgical outcomes in LDHP via UMI. The established phase (n=69, since case #33) had a significantly shorter operative time, a smaller incision size, and less blood loss than the previous learning phase (n=32, serial case number up to the last 19th left lobe case). Multivariate analysis showed that the learning phase, high body mass index ≥25 kg/m 2 , and left lobe graft procurement are the factors associated with surgical events including operative blood loss ≥400 mL, operative time ≥300 minutes, or surgical complications ≥Clavien-Dindo grade II. There is an obvious learning curve in performing LDHP via UMI, and 32 cases including both 19 cases for left lobe and nine cases for right lobe are needed for having stable and acceptable surgical outcomes. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A marked point process approach for identifying neural correlates of tics in Tourette Syndrome.

PubMed

Loza, Carlos A; Shute, Jonathan B; Principe, Jose C; Okun, Michael S; Gunduz, Aysegul

2017-07-01

We propose a novel interpretation of local field potentials (LFP) based on a marked point process (MPP) framework that models relevant neuromodulations as shifted weighted versions of prototypical temporal patterns. Particularly, the MPP samples are categorized according to the well known oscillatory rhythms of the brain in an effort to elucidate spectrally specific behavioral correlates. The result is a transient model for LFP. We exploit data-driven techniques to fully estimate the model parameters with the added feature of exceptional temporal resolution of the resulting events. We utilize the learned features in the alpha and beta bands to assess correlations to tic events in patients with Tourette Syndrome (TS). The final results show stronger coupling between LFP recorded from the centromedian-paraficicular complex of the thalamus and the tic marks, in comparison to electrocorticogram (ECoG) recordings from the hand area of the primary motor cortex (M1) in terms of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

Optimized color decomposition of localized whole slide images and convolutional neural network for intermediate prostate cancer classification

NASA Astrophysics Data System (ADS)

Zhou, Naiyun; Gao, Yi

2017-03-01

This paper presents a fully automatic approach to grade intermediate prostate malignancy with hematoxylin and eosin-stained whole slide images. Deep learning architectures such as convolutional neural networks have been utilized in the domain of histopathology for automated carcinoma detection and classification. However, few work show its power in discriminating intermediate Gleason patterns, due to sporadic distribution of prostate glands on stained surgical section samples. We propose optimized hematoxylin decomposition on localized images, followed by convolutional neural network to classify Gleason patterns 3+4 and 4+3 without handcrafted features or gland segmentation. Crucial glands morphology and structural relationship of nuclei are extracted twice in different color space by the multi-scale strategy to mimic pathologists' visual examination. Our novel classification scheme evaluated on 169 whole slide images yielded a 70.41% accuracy and corresponding area under the receiver operating characteristic curve of 0.7247.

Probabilistic Reinforcement Learning in Adults with Autism Spectrum Disorders

PubMed Central

Solomon, Marjorie; Smith, Anne C.; Frank, Michael J.; Ly, Stanford; Carter, Cameron S.

2017-01-01

Background Autism spectrum disorders (ASDs) can be conceptualized as disorders of learning, however there have been few experimental studies taking this perspective. Methods We examined the probabilistic reinforcement learning performance of 28 adults with ASDs and 30 typically developing adults on a task requiring learning relationships between three stimulus pairs consisting of Japanese characters with feedback that was valid with different probabilities (80%, 70%, and 60%). Both univariate and Bayesian state–space data analytic methods were employed. Hypotheses were based on the extant literature as well as on neurobiological and computational models of reinforcement learning. Results Both groups learned the task after training. However, there were group differences in early learning in the first task block where individuals with ASDs acquired the most frequently accurately reinforced stimulus pair (80%) comparably to typically developing individuals; exhibited poorer acquisition of the less frequently reinforced 70% pair as assessed by state–space learning curves; and outperformed typically developing individuals on the near chance (60%) pair. Individuals with ASDs also demonstrated deficits in using positive feedback to exploit rewarded choices. Conclusions Results support the contention that individuals with ASDs are slower learners. Based on neurobiology and on the results of computational modeling, one interpretation of this pattern of findings is that impairments are related to deficits in flexible updating of reinforcement history as mediated by the orbito-frontal cortex, with spared functioning of the basal ganglia. This hypothesis about the pathophysiology of learning in ASDs can be tested using functional magnetic resonance imaging. PMID:21425243

Non-Constant Learning Rates in Retrospective Experience Curve Analyses and their Correlation to Deployment Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Max; Smith, Sarah J.; Sohn, Michael D.

2015-07-16

A key challenge for policy-makers and technology market forecasters is to estimate future technology costs and in particular the rate of cost reduction versus production volume. A related, critical question is what role should state and federal governments have in advancing energy efficient and renewable energy technologies? This work provides retrospective experience curves and learning rates for several energy-related technologies, each of which have a known history of federal and state deployment programs. We derive learning rates for eight technologies including energy efficient lighting technologies, stationary fuel cell systems, and residential solar photovoltaics, and provide an overview and timeline ofmore » historical deployment programs such as state and federal standards and state and national incentive programs for each technology. Piecewise linear regimes are observed in a range of technology experience curves, and public investments or deployment programs are found to be strongly correlated to an increase in learning rate across multiple technologies. A downward bend in the experience curve is found in 5 out of the 8 energy-related technologies presented here (electronic ballasts, magnetic ballasts, compact fluorescent lighting, general service fluorescent lighting, and the installed cost of solar PV). In each of the five downward-bending experience curves, we believe that an increase in the learning rate can be linked to deployment programs to some degree. This work sheds light on the endogenous versus exogenous contributions to technological innovation and highlights the impact of exogenous government sponsored deployment programs. This work can inform future policy investment direction and can shed light on market transformation and technology learning behavior.« less

Free Recall Curves: Nothing but Rehearsing Some Items More or Recalling Them Sooner?

ERIC Educational Resources Information Center

Brodie, Delbert A.; Prytulak, Lubomir S.

1975-01-01

The hypothesis that free recall curves reflecting effects of serial position, presentation time and delay of recall are attributable to subjects' pattern of rehearsal was explored. Experiments varied the patterns of rehearsal to examine the effects on recall. (CHK)

Using Technology in Teacher Preparation: Two Mature Teacher Educators Negotiate the Steep Learning Curve

ERIC Educational Resources Information Center

Monroe, Eula; Tolman, Marvin

2004-01-01

This paper chronicles the ventures of two mature faculty members who continue to negotiate their own steep learning curves in helping teacher education students use current technology. It describes the scaffolding provided within the university setting for the faculty members' growth. Included are elements supported by a PT3 grant that have…

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

PubMed

Wang, Duolin; Zeng, Shuai; Xu, Chunhui; Qiu, Wangren; Liang, Yanchun; Joshi, Trupti; Xu, Dong

2017-12-15

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction. We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data. MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep. xudong@missouri.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Conditional withholding of proboscis extension in honeybees (Apis mellifera) during discriminative punishment.

PubMed

Smith, B H; Abramson, C I; Tobin, T R

1991-12-01

Proboscis extension conditioning of honeybee workers was used to test the ability of bees to respond to appetitive and aversive stimuli while restrained in a harness that allows subjects to move their antennae and mouthparts (Kuwabara, 1957; Menzel, Erber, & Masuhr, 1974). Subjects were conditioned to discriminate between two odors, one associated with sucrose feeding and the other associated with a 10 V AC shock if they responded to the sucrose unconditioned stimulus (US) in the context of that odor. Most Ss readily learned to respond to the odor followed by sucrose feeding and not to the odor associated with sucrose stimulation plus shock. Furthermore, in the context of the odor associated with shock, significantly more subjects withheld or delayed proboscis extension on stimulation with the sucrose US than they did in the context of the odor associated with feeding. Thus, restrained honeybees can readily learn to avoid shock according to an odor context by withholding proboscis extension to a normally powerful releaser. Analysis of individual learning curves revealed that subjects differed markedly in performance on this task. Some learn the discrimination quickly, whereas others show different kinds of response patterns.

Evaluating the Bias of Alternative Cost Progress Models: Tests Using Aerospace Industry Acquisition Programs

DTIC Science & Technology

1992-12-01

suspect :mat, -n2 extent predict:.on cas jas ccsiziveiv crrei:=e amonc e v:arious models, :he fandom *.;aik, learn ha r ur e, i;<ea- variable and Bemis...Functions, Production Rate Adjustment Model, Learning Curve Model. Random Walk Model. Bemis Model. Evaluating Model Bias, Cost Prediction Bias. Cost...of four cost progress models--a random walk model, the tradiuonai learning curve model, a production rate model Ifixed-variable model). and a model

The implications of renewable energy research and development: Policy scenario analysis with experience and learning effects

NASA Astrophysics Data System (ADS)

Kobos, Peter Holmes

This dissertation analyzes the current and potential future costs of renewable energy technology from an institutional perspective. The central hypothesis is that reliable technology cost forecasting can be achieved through standard and modified experience curves implemented in a dynamic simulation model. Additionally, drawing upon region-specific institutional lessons highlights the role of market, social, and political institutions throughout an economy. Socio-political influences and government policy pathways drive resource allocation decisions that may be predominately influenced by factors other than those considered in a traditional market-driven, mechanistic approach. Learning in economic systems as a research topic is an attractive complement to the notion of institutional pathways. The economic implications of learning by doing, as first outlined by Arrow (1962), highlight decreasing production costs as individuals, or more generally the firm, become more familiar with a production process. The standard approach in the literature has been to employ a common experience curve where cumulative production is the only independent variable affecting costs. This dissertation develops a two factor experience curve, adding research, development and demonstration (RD&D) expenditures as a second variable. To illustrate the concept in the context of energy planning, two factor experience curves are developed for wind energy technology and solar photovoltaic (PV) modules under different assumptions on learning rates for cumulative capacity and the knowledge stock (a function of past RD&D efforts). Additionally, a one factor experience curve and cost trajectory scenarios are developed for concentrated solar power and geothermal energy technology, respectively. Cost forecasts are then developed for all four of these technologies in a dynamic simulation model. Combining the theoretical framework of learning by doing with the fields of organizational learning and institutional economics, this dissertation argues that the current state of renewable energy technology costs is largely due to the past production efforts (learning by doing) and RD&D efforts (learning by searching) in these global industries. This cost pathway, however, may be altered through several policy process feedback mechanisms including targeted RD&D expenditures, maintenance of RD&D to promote learning effects, and financial incentive programs that support energy production from renewable energy technologies.

Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome.

PubMed

Liu, Yun; Scirica, Benjamin M; Stultz, Collin M; Guttag, John V

2016-10-06

Frequency domain measures of heart rate variability (HRV) are associated with adverse events after a myocardial infarction. However, patterns in the traditional frequency domain (measured in Hz, or cycles per second) may capture different cardiac phenomena at different heart rates. An alternative is to consider frequency with respect to heartbeats, or beatquency. We compared the use of frequency and beatquency domains to predict patient risk after an acute coronary syndrome. We then determined whether machine learning could further improve the predictive performance. We first evaluated the use of pre-defined frequency and beatquency bands in a clinical trial dataset (N = 2302) for the HRV risk measure LF/HF (the ratio of low frequency to high frequency power). Relative to frequency, beatquency improved the ability of LF/HF to predict cardiovascular death within one year (Area Under the Curve, or AUC, of 0.730 vs. 0.704, p < 0.001). Next, we used machine learning to learn frequency and beatquency bands with optimal predictive power, which further improved the AUC for beatquency to 0.753 (p < 0.001), but not for frequency. Results in additional validation datasets (N = 2255 and N = 765) were similar. Our results suggest that beatquency and machine learning provide valuable tools in physiological studies of HRV.

Diversions: Hilbert and Sierpinski Space-Filling Curves, and beyond

ERIC Educational Resources Information Center

Gough, John

2012-01-01

Space-filling curves are related to fractals, in that they have self-similar patterns. Such space-filling curves were originally developed as conceptual mathematical "monsters", counter-examples to Weierstrassian and Reimannian treatments of calculus and continuity. These were curves that were everywhere-connected but…

The Predictive Value of Ultrasound Learning Curves Across Simulated and Clinical Settings.

PubMed

Madsen, Mette E; Nørgaard, Lone N; Tabor, Ann; Konge, Lars; Ringsted, Charlotte; Tolsgaard, Martin G

2017-01-01

The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. Twenty midwives completed a simulation-based training program in transvaginal sonography. The training was conducted on a VR simulator as well as on a physical mannequin. A subgroup of 6 participants underwent subsequent clinical training. During each of the 3 steps, the participants' performance was assessed using instruments with established validity evidence, and they advanced to the next level only after attaining predefined levels of performance. The number of repetitions and time needed to achieve predefined performance levels were recorded along with the performance scores in each setting. Finally, the outcomes were correlated across settings. A good correlation was found between time needed to achieve predefined performance levels on the VR simulator and the physical mannequin (Pearson correlation coefficient .78; P < .001). Performance scores on the VR simulator correlated well to the clinical performance scores (Pearson correlation coefficient .81; P = .049). No significant correlations were found between numbers of attempts needed to reach proficiency across the 3 different settings. A post hoc analysis found that the 50% fastest trainees at reaching proficiency during simulation-based training received higher clinical performance scores compared to trainees with scores placing them among the 50% slowest (P = .025). Performances during simulation-based sonography training may predict performance in related tasks and subsequent clinical learning curves. © 2016 by the American Institute of Ultrasound in Medicine.

Evaluation of the learning curve for external cephalic version using cumulative sum analysis

PubMed Central

Kim, So Yun; Chang, Eun Hye; Kwak, Dong Wook; Ahn, Hyun Kyung; Ryu, Hyun Mi; Kim, Moon Young

2017-01-01

Objective We evaluated the learning curve for external cephalic version (ECV) using learning curve-cumulative sum (LC-CUSUM) analysis. Methods This was a retrospective study involving 290 consecutive cases between October 2013 and March 2017. We evaluated the learning curve for ECV on nulli and over para 1 group using LC-CUSUM analysis on the assumption that 50% and 70% of ECV procedures succeeded by description a trend-line of quadratic function with reliable R2 values. Results The overall success rate for ECV was 64.8% (188/290), while the success rate for nullipara and over para 1 groups was 56.2% (100/178) and 78.6% (88/112), respectively. ‘H’ value, that the actual failure rate does not differ from the acceptable failure rate, was −3.27 and −1.635 when considering ECV success rates of 50% and 70%, respectively. Consequently, in order to obtain a consistent 50% success rate, we would require 57 nullipara cases, and in order to obtain a consistent 70% success rate, we would require 130 nullipara cases. In contrast, 8 to 10 over para 1 cases would be required for an expected success rate of 50% and 70% on over para 1 group. Conclusion Even a relatively inexperienced physician can experience success with multipara and after accumulating experience, they will manage nullipara cases. Further research is required for LC-CUSUM involving several practitioners instead of a single practitioner. This will lead to the gradual implementation of standard learning curve guidelines for ECV. PMID:28791265

An object location memory paradigm for older adults with and without mild cognitive impairment.

PubMed

Külzow, Nadine; Kerti, Lucia; Witte, Veronica A; Kopp, Ute; Breitenstein, Caterina; Flöel, Agnes

2014-11-30

Object-location memory is critical in every-day life and known to deteriorate early in the course of neurodegenerative disease. We adapted the previously established learning paradigm "LOCATO" for use in healthy older adults and patients with mild cognitive impairment (MCI). Pictures of real-life buildings were associated with positions on a two-dimensional street map by repetitions of "correct" object-location pairings over the course of five training blocks, followed by a recall task. Correct/incorrect associations were indicated by button presses. The original two 45-item sets were reduced to 15 item-sets, and tested in healthy older adults and MCI for learning curve, recall, and re-test effects. The two 15-item versions showed comparable learning curves and recall scores within each group. While learning curves increased linearly in both groups, MCI patients performed significantly worse on learning and recall compared to healthy controls. Re-testing after 6 month showed small practice effects only. LOCATO is a simple standardized task that overcomes several limitation of previously employed visuospatial task by using real-life stimuli, minimizing verbal encoding, avoiding fine motor responses, combining explicit and implicit statistical learning, and allowing to assess learning curve in addition to recall. Results show that the shortened version of LOCATO meets the requirements for a robust and ecologically meaningful assessment of object-location memory in older adults with and without MCI. It can now be used to systematically assess acquisition of object-location memory and its modulation through adjuvant therapies like pharmacological or non-invasive brain stimulation. Copyright © 2014 Elsevier B.V. All rights reserved.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis

PubMed Central

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

Background The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. Methods and finding We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755–0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691–0.783) and 0.742 (0.698–0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. Conclusions According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction. PMID:28060903

[Individual learning curve for radical robot-assisted prostatectomy based on the example of three professionals working in one clinic].

PubMed

Rasner, P I; Pushkar', D Iu; Kolontarev, K B; Kotenkov, D V

2014-01-01

The appearance of new surgical technique always requires evaluation of its effectiveness and ease of acquisition. A comparative study of the results of the first three series of successive robot-assisted radical prostatectomy (RARP) performed on at time by three surgeons, was conducted. The series consisted of 40 procedures, and were divided into 4 groups of 10 operations for the analysis. When comparing data, statistically significant improvement of intra- and postoperative performance in each series was revealed, with increase in the number of operations performed, and in each subsequent series compared with the preceding one. We recommend to perform the planned conversion at the first operation. In our study, previous laparoscopic experience did not provide any significant advantages in the acquisition of robot-assisted technology. To characterize the individual learning curve, we recommend the use of the number of operations that the surgeon looked in the life-surgery regimen and/or in which he participated as an assistant before his own surgical activity, as well as the indicator "technical defect". In addition to the term "individual learning curve", we propose to introduce the terms "surgeon's individual training phase", and "clinic's learning curve".

Learning curve for new technology?: a nationwide register-based study of 46,363 total knee arthroplasties.

PubMed

Peltola, Mikko; Malmivaara, Antti; Paavola, Mika

2013-12-04

The risk of early revision is increased for the first patients operatively treated with a newly introduced knee prosthesis. In this study, we explored the learning curves associated with ten knee implant models to determine their effect on early revision risk. We studied register data from all seventy-five surgical units that performed knee arthroplasty in Finland from 1998 to 2007. Of 54,925 patients (66,098 knees), 39,528 patients (46,363 knees) underwent arthroplasty for osteoarthritis of the knee with the ten most common total knee implants and were followed with complete data until December 31, 2010, or the time of death. We used a Cox proportional-hazards regression model for calculating the hazard ratios for early revision for the first fifteen arthroplasties and subsequent increments of numbers of arthroplasties. We found large differences among knee implants at the introduction with regard to the risk of early revision, as well as for the overall risk of early revision. A learning curve was found for four implant models, while six models did not show a learning effect on the risk of early revision. The survivorship of the studied prostheses showed substantial differences. Knee implants have model-specific learning curves and early revision risks. Some models are more difficult to implement than others. The manufacturers should consider the learning effect when designing implants and instrumentation. The surgeons should thoroughly familiarize themselves with the new knee implants before use.

Analysis of the learning curve for peroral endoscopic myotomy for esophageal achalasia: Single-center, two-operator experience.

PubMed

Lv, Houning; Zhao, Ningning; Zheng, Zhongqing; Wang, Tao; Yang, Fang; Jiang, Xihui; Lin, Lin; Sun, Chao; Wang, Bangmao

2017-05-01

Peroral endoscopic myotomy (POEM) has emerged as an advanced technique for the treatment of achalasia, and defining the learning curve is mandatory. From August 2011 to June 2014, two operators in our institution (A&B) carried out POEM on 35 and 33 consecutive patients, respectively. Moving average and cumulative sum (CUSUM) methods were used to analyze the POEM learning curve for corrected operative time (cOT), referring to duration of per centimeter myotomy. Additionally, perioperative outcomes were compared among distinct learning curve phases. Using the moving average method, cOT reached a plateau at the 29th case and at the 24th case for operators A and B, respectively. CUSUM analysis identified three phases: initial learning period (Phase 1), efficiency period (Phase 2) and mastery period (Phase 3). The relatively smooth state in the CUSUM graph occurred at the 26th case and at the 24th case for operators A and B, respectively. Mean cOT of distinct phases for operator A were 8.32, 5.20 and 3.97 min, whereas they were 5.99, 3.06 and 3.75 min for operator B, respectively. Eckardt score and lower esophageal sphincter pressure significantly decreased during the 1-year follow-up period. Data were comparable regarding patient characteristics and perioperative outcomes. This single-center study demonstrated that expert endoscopists with experience in esophageal endoscopic submucosal dissection reached a plateau in learning of POEM after approximately 25 cases. © 2016 Japan Gastroenterological Endoscopy Society.

GENERATING FRACTAL PATTERNS BY USING p-CIRCLE INVERSION

NASA Astrophysics Data System (ADS)

Ramírez, José L.; Rubiano, Gustavo N.; Zlobec, Borut Jurčič

2015-10-01

In this paper, we introduce the p-circle inversion which generalizes the classical inversion with respect to a circle (p = 2) and the taxicab inversion (p = 1). We study some basic properties and we also show the inversive images of some basic curves. We apply this new transformation to well-known fractals such as Sierpinski triangle, Koch curve, dragon curve, Fibonacci fractal, among others. Then we obtain new fractal patterns. Moreover, we generalize the method called circle inversion fractal be means of the p-circle inversion.

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed Central

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students. PMID:28559866

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students.

The Parallel Episodic Processing (PEP) model 2.0: A single computational model of stimulus-response binding, contingency learning, power curves, and mixing costs.

PubMed

Schmidt, James R; De Houwer, Jan; Rothermund, Klaus

2016-12-01

The current paper presents an extension of the Parallel Episodic Processing model. The model is developed for simulating behaviour in performance (i.e., speeded response time) tasks and learns to anticipate both how and when to respond based on retrieval of memories of previous trials. With one fixed parameter set, the model is shown to successfully simulate a wide range of different findings. These include: practice curves in the Stroop paradigm, contingency learning effects, learning acquisition curves, stimulus-response binding effects, mixing costs, and various findings from the attentional control domain. The results demonstrate several important points. First, the same retrieval mechanism parsimoniously explains stimulus-response binding, contingency learning, and practice effects. Second, as performance improves with practice, any effects will shrink with it. Third, a model of simple learning processes is sufficient to explain phenomena that are typically (but perhaps incorrectly) interpreted in terms of higher-order control processes. More generally, we argue that computational models with a fixed parameter set and wider breadth should be preferred over those that are restricted to a narrow set of phenomena. Copyright © 2016 Elsevier Inc. All rights reserved.

The Relation Between Rotation Deformity and Nerve Root Stress in Lumbar Scoliosis

NASA Astrophysics Data System (ADS)

Kim, Ho-Joong; Lee, Hwan-Mo; Moon, Seong-Hwan; Chun, Heoung-Jae; Kang, Kyoung-Tak

Even though several finite element models of lumbar spine were introduced, there has been no model including the neural structure. Therefore, the authors made the novel lumbar spine finite element model including neural structure. Using this model, we investigated the relation between the deformity pattern and nerve root stress. Two lumbar models with different types of curve pattern (lateral bending and lateral bending with rotation curve) were made. In the model of lateral bending curves without rotation, the principal compressive nerve root stress on the concave side was greater than the principal tensile stress on the convex side at the apex vertebra. Contrarily, in the lateral bending curve with rotational deformity, the nerve stress on the convex side was higher than that on the concave side. Therefore, this study elicit that deformity pattern could have significantly influence on the nerve root stress in the lumbar spine.

From Experiment to Theory: What Can We Learn from Growth Curves?

PubMed

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Transforaminal Lumbar Interbody Fusion with Rigid Interspinous Process Fixation: A Learning Curve Analysis of a Surgeon Team's First 74 Cases.

PubMed

Doherty, Patrick; Welch, Arthur; Tharpe, Jason; Moore, Camille; Ferry, Chris

2017-05-30

Studies have shown that a significant learning curve may be associated with adopting minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) with bilateral pedicle screw fixation (BPSF). Accordingly, several hybrid TLIF techniques have been proposed as surrogates to the accepted BPSF technique, asserting that less/fewer fixation(s) or less disruptive fixation may decrease the learning curve while still maintaining the minimally disruptive benefits. TLIF with interspinous process fixation (ISPF) is one such surrogate procedure. However, despite perceived ease of adaptability given the favorable proximity of the spinous processes, no evidence exists demonstrating whether or not the technique may possess its own inherent learning curve. The purpose of this study was to determine whether an intraoperative learning curve for one- and two-level TLIF + ISPF may exist for a single lead surgeon. Seventy-four consecutive patients who received one- or two-Level TLIF with rigid ISPF by a single lead surgeon were retrospectively reviewed. It was the first TLIF + ISPF case series for the lead surgeon. Intraoperative blood loss (EBL), hospitalization length-of-stay (LOS), fluoroscopy time, and postoperative complications were collected. EBL, LOS, and fluoroscopy time were modeled as a function of case number using multiple linear regression methods. A change point was included in each model to allow the trajectory of the outcomes to change during the duration of the case series. These change points were determined using profile likelihood methods. Models were fit using the maximum likelihood estimates for the change points. Age, sex, body mass index (BMI), and the number of treated levels were included as covariates. EBL, LOS, and fluoroscopy time did not significantly differ by age, sex, or BMI (p ≥ 0.12). Only EBL differed significantly by the number of levels (p = 0.026). The case number was not a significant predictor of EBL, LOS, or fluoroscopy time (p ≥ 0.21). At the time of data collection (mean time from surgery: 13.3 months), six patients had undergone revision due to interbody migration. No ISPF device complications were observed. Study outcomes support the ideal that TLIF + ISPF can be a readily adopted procedure without a significant intraoperative learning curve. However, the authors emphasize that further assessment of long-term healing outcomes is essential in fully characterizing both the efficacy and the indication learning curve for the TLIF + ISPF technique.

Clinical and Radiographic Outcomes With Assessment of the Learning Curve in Arthroscopically Assisted Latissimus Dorsi Tendon Transfer for Irreparable Posterosuperior Rotator Cuff Tears.

PubMed

Yamakado, Kotaro

2017-12-01

To evaluate the clinical results of an arthroscopy-assisted latissimus dorsi tendon transfer (aLD) for irreparable posterosuperior cuff tears as a primary surgery. The secondary aim of this study was to quantify the learning curve using the log-linear model. We hypothesized that aLD significantly improved shoulder function and that there was consistent reduction of the operative time in support of a learning-curve effect. After the arthroscopic partial repair was completed, the latissimus dorsi tendon was harvested via axillary mini-open incision and fixed with a knotless anchor arthroscopically. All patients were evaluated preoperatively and postoperatively using a modified University of California Los Angeles (UCLA) scoring system, active range of motion, and the visual analog scale (VAS) for pain. The operative time was recorded to quantify the learning curve using a log-linear model. Thirty patients with a mean age of 67.4 years who underwent aLD were included. At a mean of 34 months after an aLD, the mean UCLA score increased from 15.7 preoperatively to 28.8 postoperatively (P < .001). The mean active forward elevation increased from 105° preoperatively to 149° postoperatively (P < .001). The mean active external rotation increased from 22° preoperatively to 32° postoperatively (P < .001). The VAS improved from 58 mm to 18 mm (P < .001). In all but 2 cases (93%), the preoperative osteoarthritis grade was maintained. The mean operative time was 145 minutes. A significant linear correlation was observed between the operative time and cumulative volume of cases after performing a logarithmic transformation. The learning rate was calculated as 84%. Arthroscopy-assisted latissimus dorsi tendon transfer is a technically demanding procedure; however, it can lead to significant improvements in overall shoulder pain and function. This study also confirmed a learning-curve effect for the aLD. The learning rate was 84%, indicating the existence of a long learning period. Level IV, therapeutic case series. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis

PubMed Central

Stepanov, Igor I.; Abramson, Charles I.; Hoogs, Marietta; Benedict, Ralph H. B.

2012-01-01

The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1–5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(−B2  ∗  (X − 1)) + B4  ∗  (1 − exp(−B2  ∗  (X − 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both. PMID:22745911

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis.

PubMed

Stepanov, Igor I; Abramson, Charles I; Hoogs, Marietta; Benedict, Ralph H B

2012-01-01

The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1-5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(-B2  ∗  (X - 1)) + B4  ∗  (1 - exp(-B2  ∗  (X - 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both.

Using Machine Learning To Predict Which Light Curves Will Yield Stellar Rotation Periods

NASA Astrophysics Data System (ADS)

Agüeros, Marcel; Teachey, Alexander

2018-01-01

Using time-domain photometry to reliably measure a solar-type star's rotation period requires that its light curve have a number of favorable characteristics. The probability of recovering a period will be a non-linear function of these light curve features, which are either astrophysical in nature or set by the observations. We employ standard machine learning algorithms (artificial neural networks and random forests) to predict whether a given light curve will produce a robust rotation period measurement from its Lomb-Scargle periodogram. The algorithms are trained and validated using salient statistics extracted from both simulated light curves and their corresponding periodograms, and we apply these classifiers to the most recent Intermediate Palomar Transient Factory (iPTF) data release. With this pipeline, we anticipate measuring rotation periods for a significant fraction of the ∼4x108 stars in the iPTF footprint.

Oscillatory patterns in the light curves of five long-term monitored type 1 active galactic nuclei

NASA Astrophysics Data System (ADS)

Kovačević, Andjelka B.; Pérez-Hernández, Ernesto; Popović, Luka Č.; Shapovalova, Alla I.; Kollatschny, Wolfram; Ilić, Dragana

2018-04-01

New combined data of five well-known type 1 active galactic nuclei (AGNs) are probed with a novel hybrid method in a search for oscillatory behaviour. Additional analysis of artificial light curves obtained from the coupled oscillatory models gives confirmation for detected periods that could have a physical background. We find periodic variations in the long-term light curves of 3C 390.3, NGC 4151 and NGC 5548, and E1821 + 643, with correlation coefficients larger than 0.6. We show that the oscillatory patterns of two binary black hole candidates, NGC 5548 and E1821 + 643, correspond to qualitatively different dynamical regimes of chaos and stability, respectively. We demonstrate that the absence of oscillatory patterns in Arp 102B could be the result of a weak coupling between oscillatory mechanisms. This is the first good evidence that 3C 390.3 and Arp 102B, categorized as double-peaked Balmer line objects, have qualitative different dynamics. Our analysis shows a novelty in the oscillatory dynamical patterns of the light curves of these type 1 AGNs.

Why the Kantian ideal survives medical learning curves, and why it matters.

PubMed

Brecher, B

2006-09-01

The "Kantian ideal" is often misunderstood as invoking individual autonomy rather than rational self legislation. Le Morvan and Stock's otherwise insightful discussion of "Medical learning curves and the Kantian ideal"--for example--draws the mistaken inference that that ideal is inconsistent with the realities of medical practice. But it is not. Rationally to be a patient entails accepting its necessary conditions.

A Method for Writing Open-Ended Curved Arrow Notation Questions for Multiple-Choice Exams and Electronic-Response Systems

ERIC Educational Resources Information Center

Ruder, Suzanne M.; Straumanis, Andrei R.

2009-01-01

A critical stage in the process of developing a conceptual understanding of organic chemistry is learning to use curved arrow notation. From this stems the ability to predict reaction products and mechanisms beyond the realm of memorization. Since evaluation (i.e., testing) is known to be a key driver of student learning, it follows that a new…

Evaluation of the learning curve of laparoscopic choledochal cyst excision and Roux-en-Y hepaticojejunostomy in children: CUSUM analysis of a single surgeon's experience.

PubMed

Wen, Zhe; Liang, Huiying; Liang, Jiankun; Liang, Qifeng; Xia, Huimin

2017-02-01

Laparoscopic cyst excision and Roux-en-Y hepaticojejunostomy is gaining popularity as a treatment for choledochal cyst (CDC) in children. However, the learning curve for this challenging laparoscopic procedure has not been addressed. The aim of this study is to determine the characteristics of the learning curve of this procedure. This may guide the training in institutions currently not using this technique. A prospectively collected database comprising all medical records of the first 104 consecutive patients undergoing laparoscopic CDC excision and Roux-en-Y hepaticojejunostomy performed by one surgeon was studied. Multifactorial linear/logistic regression analysis was performed to identify patient-, surgeon-, and procedure-related factors associated with operating times, rates of adverse event, and length of postoperative stay. Cumulative sum analysis demonstrated a learning curve for laparoscopic choledochal cyst excision of 37 cases. Comparing the early with the late experiences (37 vs. 67 cases), the surgeon-specific outcomes significantly improved in terms of operating times (352 vs. 240 min; P < 0.001), postoperative complication rate (13.5 vs. 1.5 %; P = 0.02), and the length of hospital stay (9.4 vs. 7.8 days; P = 0.01). After multivariate analyses, independent predictors of operating times included the completion of the learning curve (CLC) (OR 0.68, 95 % CI 0.63-0.73) and adhesion score (OR middle 1.25, 95 % CI 1.08-1.45; OR high 1.40, 95 % CI 1.20-1.62; compared with the low score); significant predictors of perioperative adverse outcomes were CLC (OR 0.07, 95 % CI 0.02-0.34) and comorbidities prior to the surgery (OR 30.65, 95 % CI 1.71-549.63). The independent predictors of length of postoperative stay included CLC, preoperative comorbidities, and perioperative adverse events. CLC for laparoscopic choledochal cyst excision is 37 cases. After CLC, not only the operative time is reduced, the complications, adverse results, and the length of hospital stay all decreased significantly. The learning curve can be used as the basis for performance guiding the training.

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Learning curve of single port laparoscopic cholecystectomy determined using the non-linear ordinary least squares method based on a non-linear regression model: An analysis of 150 consecutive patients.

PubMed

Han, Hyung Joon; Choi, Sae Byeol; Park, Man Sik; Lee, Jin Suk; Kim, Wan Bae; Song, Tae Jin; Choi, Sang Yong

2011-07-01

Single port laparoscopic surgery has come to the forefront of minimally invasive surgery. For those familiar with conventional techniques, however, this type of operation demands a different type of eye/hand coordination and involves unfamiliar working instruments. Herein, the authors describe the learning curve and the clinical outcomes of single port laparoscopic cholecystectomy for 150 consecutive patients with benign gallbladder disease. All patients underwent single port laparoscopic cholecystectomy using a homemade glove port by one of five operators with different levels of experiences of laparoscopic surgery. The learning curve for each operator was fitted using the non-linear ordinary least squares method based on a non-linear regression model. Mean operating time was 77.6 ± 28.5 min. Fourteen patients (6.0%) were converted to conventional laparoscopic cholecystectomy. Complications occurred in 15 patients (10.0%), as follows: bile duct injury (n = 2), surgical site infection (n = 8), seroma (n = 2), and wound pain (n = 3). One operator achieved a learning curve plateau at 61.4 min per procedure after 8.5 cases and his time improved by 95.3 min as compared with initial operation time. Younger surgeons showed significant decreases in mean operation time and achieved stable mean operation times. In particular, younger surgeons showed significant decreases in operation times after 20 cases. Experienced laparoscopic surgeons can safely perform single port laparoscopic cholecystectomy using conventional or angled laparoscopic instruments. The present study shows that an operator can overcome the single port laparoscopic cholecystectomy learning curve in about eight cases.

Evaluating the learning curve for robot-assisted laparoscopic radical cystectomy.

PubMed

Pruthi, Raj S; Smith, Angela; Wallen, Eric M

2008-11-01

We seek to describe the learning curve of robot-assisted laparoscopic radical cystectomy by evaluating some of the surgical, oncologic, and clinical outcomes in our initial experience with 50 consecutive patients undergoing this novel procedure. Fifty consecutive patients (representing our initial experience with robot-assisted cystectomy) underwent radical cystectomy and urinary diversion from January 2006 to December 2007. Several different metrics were used to evaluate the learning curve of this procedure, including estimated blood loss (EBL), operative (OR) time, pathologic outcomes, and complication rate. We evaluated patients as a continuous variable, divided into five distinct time periods (quintiles), and stratified by first half and second half of robotic experience. EBL was not significantly lower until the third quintile (patients 21-30), after which further significant reductions were not observed. Mean OR time declined between each quintile for the first 30 patients (1-10 v 11-20 v 21-30). No significant declines occurred after the third quintile (21-30). When evaluated as a continuous variable, the statistical cut point at which no further significant reductions were observed was after patient 20 for OR time. No differences were observed with regard to time to flatus, bowel movement, or hospital discharge. Furthermore, complications were not different between the initial 25 patients and the most recent patients. There has been no case of a positive margin, and there was only one inadvertent bladder entry. Lymph node yield has also not significantly changed over time. This report helps to define the learning curve associated with robot-assisted laparoscopic radical cystectomy for bladder cancer. Despite the higher OR times and blood loss that is observed early in the learning curve, no such compromises are observed with regard to these oncologic parameters even early in the experience.

Robotic Mitral Valve Repair: The Learning Curve.

PubMed

Goodman, Avi; Koprivanac, Marijan; Kelava, Marta; Mick, Stephanie L; Gillinov, A Marc; Rajeswaran, Jeevanantham; Brzezinski, Anna; Blackstone, Eugene H; Mihaljevic, Tomislav

Adoption of robotic mitral valve surgery has been slow, likely in part because of its perceived technical complexity and a poorly understood learning curve. We sought to correlate changes in technical performance and outcome with surgeon experience in the "learning curve" part of our series. From 2006 to 2011, two surgeons undertook robotically assisted mitral valve repair in 458 patients (intent-to-treat); 404 procedures were completed entirely robotically (as-treated). Learning curves were constructed by modeling surgical sequence number semiparametrically with flexible penalized spline smoothing best-fit curves. Operative efficiency, reflecting technical performance, improved for (1) operating room time for case 1 to cases 200 (early experience) and 400 (later experience), from 414 to 364 to 321 minutes (12% and 22% decrease, respectively), (2) cardiopulmonary bypass time, from 148 to 102 to 91 minutes (31% and 39% decrease), and (3) myocardial ischemic time, from 119 to 75 to 68 minutes (37% and 43% decrease). Composite postoperative complications, reflecting safety, decreased from 17% to 6% to 2% (63% and 85% decrease). Intensive care unit stay decreased from 32 to 28 to 24 hours (13% and 25% decrease). Postoperative stay fell from 5.2 to 4.5 to 3.8 days (13% and 27% decrease). There were no in-hospital deaths. Predischarge mitral regurgitation of less than 2+, reflecting effectiveness, was achieved in 395 (97.8%), without correlation to experience; return-to-work times did not change substantially with experience. Technical efficiency of robotic mitral valve repair improves with experience and permits its safe and effective conduct.

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

PubMed Central

Montes, Jesus; Gomez, Elena; Merchán-Pérez, Angel; DeFelipe, Javier; Peña, Jose-Maria

2013-01-01

Chemical synaptic transmission involves the release of a neurotransmitter that diffuses in the extracellular space and interacts with specific receptors located on the postsynaptic membrane. Computer simulation approaches provide fundamental tools for exploring various aspects of the synaptic transmission under different conditions. In particular, Monte Carlo methods can track the stochastic movements of neurotransmitter molecules and their interactions with other discrete molecules, the receptors. However, these methods are computationally expensive, even when used with simplified models, preventing their use in large-scale and multi-scale simulations of complex neuronal systems that may involve large numbers of synaptic connections. We have developed a machine-learning based method that can accurately predict relevant aspects of the behavior of synapses, such as the percentage of open synaptic receptors as a function of time since the release of the neurotransmitter, with considerably lower computational cost compared with the conventional Monte Carlo alternative. The method is designed to learn patterns and general principles from a corpus of previously generated Monte Carlo simulations of synapses covering a wide range of structural and functional characteristics. These patterns are later used as a predictive model of the behavior of synapses under different conditions without the need for additional computationally expensive Monte Carlo simulations. This is performed in five stages: data sampling, fold creation, machine learning, validation and curve fitting. The resulting procedure is accurate, automatic, and it is general enough to predict synapse behavior under experimental conditions that are different to the ones it has been trained on. Since our method efficiently reproduces the results that can be obtained with Monte Carlo simulations at a considerably lower computational cost, it is suitable for the simulation of high numbers of synapses and it is therefore an excellent tool for multi-scale simulations. PMID:23894367

Can the learning curve of totally endoscopic robotic mitral valve repair be short-circuited?

PubMed

Yaffee, David W; Loulmet, Didier F; Kelly, Lauren A; Ward, Alison F; Ursomanno, Patricia A; Rabinovich, Annette E; Neuburger, Peter J; Krishnan, Sandeep; Hill, Frederick T; Grossi, Eugene A

2014-01-01

A concern with the initiation of totally endoscopic robotic mitral valve repair (TERMR) programs has been the risk for the learning curve. To minimize this risk, we initiated a TERMR program with a defined team and structured learning approach before clinical implementation. A dedicated team (two surgeons, one cardiac anesthesiologist, one perfusionist, and two nurses) was trained with clinical scenarios, simulations, wet laboratories, and "expert" observation for 3 months. This team then performed a series of TERMRs of varying complexity. Thirty-two isolated TERMRs were performed during the first programmatic year. All operations included mitral valve repair, left atrial appendage exclusion, and annuloplasty device implantation. Additional procedures included leaflet resection, neochordae insertion, atrial ablation, and papillary muscle shortening. Longer clamp times were associated with number of neochordae (P < 0.01), papillary muscle procedures (P < 0.01), and leaflet resection (P = 0.06). Sequential case number had no impact on cross-clamp time (P = 0.3). Analysis of nonclamp time demonstrated a 71.3% learning percentage (P < 0.01; ie, 28.7% reduction in nonclamp time with each doubling of case number). There were no hospital deaths or incidences of stroke, myocardial infarction, unplanned reoperation, respiratory failure, or renal failure. Median length of stay was 4 days. All patients were discharged home. Totally endoscopic robotic mitral valve repair can be safely performed after a pretraining regimen with emphasis on experts' current practice and team training. After a pretraining regimen, cross-clamp times were not subject to learning curve phenomena but were dependent on procedural complexity. Nonclamp times were associated with a short learning curve.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

PubMed

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Comparison of the learning curves of digital examination and transabdominal sonography for the determination of fetal head position during labor.

PubMed

Rozenberg, P; Porcher, R; Salomon, L J; Boirot, F; Morin, C; Ville, Y

2008-03-01

To evaluate the learning curve of transabdominal sonography for the determination of fetal head position in labor and to compare it with that of digital vaginal examination. A student midwife who had never performed digital vaginal examination or ultrasound examination was recruited for this study. Instructions on how to perform digital vaginal examination and ultrasound examination were given before and after completing the first vaginal and ultrasound examinations, and repeated for each subsequent examination for as long as necessary. Digital and ultrasound diagnoses of the fetal head position were always performed first by the student midwife, and repeated by an experienced midwife or physician. The learning curve for identification of the fetal head position by either one of the two methods was analyzed using the cumulative sums (CUSUM) method for measurement errors. One hundred patients underwent digital vaginal examination and 99 had transabdominal sonography for the determination of fetal head position. An error rate of around 50% for vaginal examination was nearly constant during the first 50 examinations. It decreased subsequently, to stabilize at a low level from the 82(nd) patient. Errors of +/- 180 degrees were the most frequent. The learning curve for ultrasound imaging stabilized earlier than that of vaginal examination, after the 32(nd) patient. The most frequent errors with ultrasound examination were the inability to conclude on a diagnosis, particularly at the beginning of training, followed by errors of +/- 45 degrees. Based on our findings for the student tested, learning and accuracy of the determination of fetal head position in labor were easier and higher, respectively, with transabdominal sonography than with digital examination. This should encourage physicians to introduce clinical ultrasound examination into their practice. CUSUM charts provide a reliable representation of the learning curve, by accumulating evidence of performance. Copyright (c) 2008 ISUOG. Published by John Wiley & Sons, Ltd.

Time-Decayed User Profile for Second Language Vocabulary Learning System

ERIC Educational Resources Information Center

Li, Li; Wei, Xiao

2014-01-01

Vocabulary learning is the foundation of second language learning. Many E-learning systems have been developed to help learners to learn vocabulary efficiently. Most of these systems employ Ebbinghaus Forgetting Curve to make the review schedule for learners. However, learners are different in learning ability and the review schedule based on…

Why the Kantian ideal survives medical learning curves, and why it matters

PubMed Central

Brecher, B

2006-01-01

The “Kantian ideal” is often misunderstood as invoking individual autonomy rather than rational self legislation. Le Morvan and Stock's otherwise insightful discussion of “Medical learning curves and the Kantian ideal”—for example—draws the mistaken inference that that ideal is inconsistent with the realities of medical practice. But it is not. Rationally to be a patient entails accepting its necessary conditions. PMID:16943330

The learning curve of laparoendoscopic single-Site (LESS) fundoplication: definable, short, and safe.

PubMed

Ross, Sharona B; Choung, Edward; Teta, Anthony F; Colibao, Lotiffa; Luberice, Kenneth; Paul, Harold; Rosemurgy, Alexander S

2013-01-01

This study of laparoendoscopic single-site (LESS) fundoplication for gastroesophageal reflux disease was undertaken to determine the "learning curve" for implementing LESS fundoplication. One hundred patients, 38% men, with a median age of 61 years and median body mass index of 26 kg/m(2) , underwent LESS fundoplications. The operative times, placement of additional trocars, conversions to "open" operations, and complications were compared among patient quartiles to establish a learning curve. Median data are reported. The median operative times and complications did not differ among 25-patient cohorts. Additional trocars were placed in 27% of patients, 67% of whom were in the first 25-patient cohort. Patients undergoing LESS fundoplication had a dramatic relief in the frequency and severity of all symptoms of reflux across all cohorts equally (P < .05), particularly for heartburn and regurgitation, without causing dysphagia. LESS fundoplication ameliorates symptoms of gastroesophageal reflux disease without apparent scarring. Notably, few operations required additional trocars after the first 25-patient cohort. Patient selection became more inclusive (eg, more "redo" fundoplications) with increasing experience, whereas operative times and complications remained relatively unchanged. The learning curve of LESS fundoplication is definable, short, and safe. We believe that patients will seek LESS fundoplication because of the efficacy and superior cosmetic outcomes; surgeons will need to meet this demand.

Prognostication of Learning Curve on Surgical Management of Vasculobiliary Injuries after Cholecystectomy

PubMed Central

Dar, Faisal Saud; Zia, Haseeb; Rafique, Muhammad Salman; Khan, Nusrat Yar; Salih, Mohammad; Hassan Shah, Najmul

2016-01-01

Background. Concomitant vascular injury might adversely impact outcomes after iatrogenic bile duct injury (IBDI). Whether a new HPB center should embark upon repair of complex biliary injuries with associated vascular injuries during learning curve is unknown. The objective of this study was to determine outcome of surgical management of IBDI with and without vascular injuries in a new HPB center during its learning curve. Methods. We retrospectively reviewed patients who underwent surgical management of IBDI at our center. A total of 39 patients were included. Patients without (Group 1) and with vascular injuries (Group 2) were compared. Outcome was defined as 90-day morbidity and mortality. Results. Median age was 39 (20–80) years. There were 10 (25.6%) vascular injuries. E2 injuries were associated significantly with high frequency of vascular injuries (66% versus 15.1%) (P = 0.01). Right hepatectomy was performed in three patients. Out of these, two had a right hepatic duct stricture and one patient had combined right arterial and portal venous injury. The number of patients who developed postoperative complications was not significantly different between the two groups (11.1% versus 23.4%) (P = 0.6). Conclusion. Learning curve is not a negative prognostic variable in the surgical management of iatrogenic vasculobiliary injuries after cholecystectomy. PMID:27525124

Emergent Properties Delineate Marine Ecosystem Perturbation and Recovery.

PubMed

Link, Jason S; Pranovi, Fabio; Libralato, Simone; Coll, Marta; Christensen, Villy; Solidoro, Cosimo; Fulton, Elizabeth A

2015-11-01

Whether there are common and emergent patterns from marine ecosystems remains an important question because marine ecosystems provide billions of dollars of ecosystem services to the global community, but face many perturbations with significant consequences. Here, we develop cumulative trophic patterns for marine ecosystems, featuring sigmoidal cumulative biomass (cumB)-trophic level (TL) and 'hockey-stick' production (cumP)-cumB curves. The patterns have a trophodynamic theoretical basis and capitalize on emergent, fundamental, and invariant features of marine ecosystems. These patterns have strong global support, being observed in over 120 marine ecosystems. Parameters from these curves elucidate the direction and magnitude of marine ecosystem perturbation or recovery; if biomass and productivity can be monitored effectively over time, such relations may prove to be broadly useful. Curve parameters are proposed as possible ecosystem thresholds, perhaps to better manage the marine ecosystems of the world. Published by Elsevier Ltd.

A comparison of lamellar and penetrating keratoplasty outcomes: a registry study.

PubMed

Coster, Douglas J; Lowe, Marie T; Keane, Miriam C; Williams, Keryn A

2014-05-01

To investigate changing patterns of practice of keratoplasty in Australia, graft survival, visual outcomes, the influence of experience, and the surgeon learning curve for endothelial keratoplasty. Observational, prospective cohort study. From a long-standing national corneal transplantation register, 13 920 penetrating keratoplasties, 858 deep anterior lamellar keratoplasties (DALKs), and 2287 endokeratoplasties performed between January 1996 and February 2013 were identified. Kaplan-Meier functions were used to assess graft survival and surgeon experience, the Pearson chi-square test was used to compare visual acuities, and linear regression was used to examine learning curves. Graft survival. The total number of corneal grafts performed annually is increasing steadily. More DALKs but fewer penetrating grafts are being performed for keratoconus, and more endokeratoplasties but fewer penetrating grafts are being performed for Fuchs' dystrophy and pseudophakic bullous keratopathy. In 2012, 1482 grafts were performed, compared with 955 in 2002, translating to a requirement for 264 extra corneal donors across the country in 2012. Comparing penetrating grafts and DALKs performed for keratoconus over the same era, both graft survival (P <0.001) and visual outcomes (P <0.001) were significantly better for penetrating grafts. Survival of endokeratoplasties performed for Fuchs' dystrophy or pseudophakic bullous keratopathy was poorer than survival of penetrating grafts for the same indications over the same era (P <0.001). Visual outcomes were significantly better for penetrating grafts than for endokeratoplasties performed for Fuchs' dystrophy (P <0.001), but endokeratoplasties achieved better visual outcomes than penetrating grafts for pseudophakic bullous keratopathy (P <0.001). Experienced surgeons (>100 registered keratoplasties) achieved significantly better survival of endokeratoplasties (P <0.001) than surgeons who had performed fewer grafts (<100 registered keratoplasties). In the hands of experienced, high-volume surgeons, endokeratoplasty failures occurred even after 100 grafts had been performed. More corneal transplants, especially DALKs and endokeratoplasties, are being performed in Australia than ever before. Survival of DALKs and endokeratoplasties is worse than the survival of penetrating grafts performed for the same indications over the same timeframe. Many endokeratoplasties fail early, but the evidence for a surgeon learning curve is unconvincing. Copyright © 2014 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

A Collection of Technical Studies Completed for the Computer-Aided Acquisition and Logistic Support (CALS) Program Fiscal Year 1988. Volume 3. CGM Registration

DTIC Science & Technology

1991-03-01

the array are used cyclically, that is when the end of the array is reached, the pattern starts over at the beginning. Dashed lines wrap around curves...the dash pattern relative to the start of the path. It is interpreted as a .distance into the dash pattern at which the pattern should be started ...cubic seldom Is drawn using the four points specified. The curve starts at the first point and ends at the fourth point; the second and third point are

Learning curve for robotic-assisted laparoscopic rectal cancer surgery.

PubMed

Jiménez-Rodríguez, Rosa M; Díaz-Pavón, José Manuel; de la Portilla de Juan, Fernando; Prendes-Sillero, Emilio; Dussort, Hisnard Cadet; Padillo, Javier

2013-06-01

One of the main uses of robotic assisted abdominal surgery is the mesorectal excision in patients with rectal cancer. The aim of the present study is to analyse the learning curve for robotic assisted laparoscopic resection of rectal cancer. We included in our study 43 consecutive rectal cancer resections (16 females and 27 males) performed from January 2008 through December 2010. Mean age of patients was 66 ± 9.0 years. Surgical procedures included both abdomino-perineal and anterior resections. We analysed the following parameters: demographic data of the patients included in the study, intra- and postoperative data, time taking to set up the robot for operations (set-up or docking time), operative time, intra- and postoperative complications, conversion rates and pathological specimen features. The learning curve was analysed using cumulative sum (CUSUM) methodology. The procedures understudied included seven abdomino-perineal resections and 36 anterior resections. In our series of patients, mean robotic set-up time was 62.9 ± 24.6 min, and the mean operative time was 197.4 ± 44.3 min. Once we applied CUSUM methodology, we obtained two graphs for CUSUM values (operating time and success), both of them showing three well-differentiated phases: phase 1 (the initial 9-11 cases), phase 2 (the middle 12 cases) and phase 3 (the remaining 20-22 cases). Phase 1 represents initial learning; phase 2 plateau represents increased competence in the use of the robotic system, and finally, phase 3 represents the period of highest skill or mastery with a reduction in docking time (p = 0.000), but a slight increase in operative time (p = 0.007). The CUSUM curve shows three phases in the learning and use of robotic assisted rectal cancer surgery which correspond to the phases of initial learning of the technique, consolidation and higher expertise or mastery. The data obtained suggest that the estimated learning curve for robotic assisted rectal cancer surgery is achieved after 21-23 cases.

Does my high blood pressure improve your survival? Overall and subgroup learning curves in health.

PubMed

Van Gestel, Raf; Müller, Tobias; Bosmans, Johan

2017-09-01

Learning curves in health are of interest for a wide range of medical disciplines, healthcare providers, and policy makers. In this paper, we distinguish between three types of learning when identifying overall learning curves: economies of scale, learning from cumulative experience, and human capital depreciation. In addition, we approach the question of how treating more patients with specific characteristics predicts provider performance. To soften collinearity problems, we explore the use of least absolute shrinkage and selection operator regression as a variable selection method and Theil-Goldberger mixed estimation to augment the available information. We use data from the Belgian Transcatheter Aorta Valve Implantation (TAVI) registry, containing information on the first 860 TAVI procedures in Belgium. We find that treating an additional TAVI patient is associated with an increase in the probability of 2-year survival by about 0.16%-points. For adverse events like renal failure and stroke, we find that an extra day between procedures is associated with an increase in the probability for these events by 0.12%-points and 0.07%-points, respectively. Furthermore, we find evidence for positive learning effects from physicians' experience with defibrillation, treating patients with hypertension, and the use of certain types of replacement valves during the TAVI procedure. Copyright © 2017 John Wiley & Sons, Ltd.

Machine Learning Techniques for Stellar Light Curve Classification

NASA Astrophysics Data System (ADS)

Hinners, Trisha A.; Tat, Kevin; Thorp, Rachel

2018-07-01

We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB of Kepler light curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature engineering approaches. Studies using machine learning in the field have been primarily done on simulated data, making our study one of the first to use real light-curve data for machine learning approaches. We tuned our data using previous work with simulated data as a template and achieved mixed results between the two approaches. Representation learning using a long short-term memory recurrent neural network produced no successful predictions, but our work with feature engineering was successful for both classification and regression. In particular, we were able to achieve values for stellar density, stellar radius, and effective temperature with low error (∼2%–4%) and good accuracy (∼75%) for classifying the number of transits for a given star. The results show promise for improvement for both approaches upon using larger data sets with a larger minority class. This work has the potential to provide a foundation for future tools and techniques to aid in the analysis of astrophysical data.

Effects of antiepileptic drugs on learning as assessed by a repeated acquisition of response sequences task in rats.

PubMed

Shannon, Harlan E; Love, Patrick L

2007-02-01

Patients with epilepsy can have impaired cognitive abilities. Antiepileptic drugs (AEDs) may contribute to the cognitive deficits observed in patients with epilepsy, and have been shown to induce cognitive impairments in healthy individuals. However, there are few systematic data on the effects of AEDs on specific cognitive domains. We have previously demonstrated that a number of AEDs can impair working memory and attention. The purpose of the present study was to evaluate the effects of AEDs on learning as measured by a repeated acquisition of response sequences task in nonepileptic rats. The GABA-related AEDs phenobarbital and chlordiazepoxide significantly disrupted performance by shifting the learning curve to the right and increasing errors, whereas tiagabine and valproate did not. The sodium channel blockers carbamazepine and phenytoin suppressed responding at higher doses, whereas lamotrigine shifted the learning curve to the right and increased errors, and topiramate was without significant effect. Levetiracetam also shifted the learning curve to the right and increased errors. The disruptions produced by triazolam, chlordiazepoxide, lamotrigine, and levetiracetam were qualitatively similar to the effects of the muscarinic cholinergic receptor antagonist scopolamine. The present results indicate that AEDs can impair learning, but there are differences among AEDs in the magnitude of the disruption in nonepileptic rats, with drugs that enhance GABA receptor function and some that block sodium channels producing the most consistent impairment of learning.

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population.

PubMed

Tomitaka, Shinichiro; Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A; Ono, Yutaka

2016-01-01

Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern.

Boundary curves of individual items in the distribution of total depressive symptom scores approximate an exponential pattern in a general population

PubMed Central

Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A.; Ono, Yutaka

2016-01-01

Background Previously, we proposed a model for ordinal scale scoring in which individual thresholds for each item constitute a distribution by each item. This lead us to hypothesize that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores follow a common mathematical model, which is expressed as the product of the frequency of the total depressive symptom scores and the probability of the cumulative distribution function of each item threshold. To verify this hypothesis, we investigated the boundary curves of the distribution of total depressive symptom scores in a general population. Methods Data collected from 21,040 subjects who had completed the Center for Epidemiologic Studies Depression Scale (CES-D) questionnaire as part of a national Japanese survey were analyzed. The CES-D consists of 20 items (16 negative items and four positive items). The boundary curves of adjacent item scores in the distribution of total depressive symptom scores for the 16 negative items were analyzed using log-normal scales and curve fitting. Results The boundary curves of adjacent item scores for a given symptom approximated a common linear pattern on a log normal scale. Curve fitting showed that an exponential fit had a markedly higher coefficient of determination than either linear or quadratic fits. With negative affect items, the gap between the total score curve and boundary curve continuously increased with increasing total depressive symptom scores on a log-normal scale, whereas the boundary curves of positive affect items, which are not considered manifest variables of the latent trait, did not exhibit such increases in this gap. Discussion The results of the present study support the hypothesis that the boundary curves of each depressive symptom score in the distribution of total depressive symptom scores commonly follow the predicted mathematical model, which was verified to approximate an exponential mathematical pattern. PMID:27761346

Learning Curves of Virtual Mastoidectomy in Distributed and Massed Practice.

PubMed

Andersen, Steven Arild Wuyts; Konge, Lars; Cayé-Thomasen, Per; Sørensen, Mads Sølvsten

2015-10-01

Repeated and deliberate practice is crucial in surgical skills training, and virtual reality (VR) simulation can provide self-directed training of basic surgical skills to meet the individual needs of the trainee. Assessment of the learning curves of surgical procedures is pivotal in understanding skills acquisition and best-practice implementation and organization of training. To explore the learning curves of VR simulation training of mastoidectomy and the effects of different practice sequences with the aim of proposing the optimal organization of training. A prospective trial with a 2 × 2 design was conducted at an academic teaching hospital. Participants included 43 novice medical students. Of these, 21 students completed time-distributed practice from October 14 to November 29, 2013, and a separate group of 19 students completed massed practice on May 16, 17, or 18, 2014. Data analysis was performed from June 6, 2014, to March 3, 2015. Participants performed 12 repeated virtual mastoidectomies using a temporal bone surgical simulator in either a distributed (practice blocks spaced in time) or massed (all practice in 1 day) training program with randomization for simulator-integrated tutoring during the first 5 sessions. Performance was assessed using a modified Welling Scale for final product analysis by 2 blinded senior otologists. Compared with the 19 students in the massed practice group, the 21 students in the distributed practice group were older (mean age, 25.1 years), more often male (15 [62%]), and had slightly higher mean gaming frequency (2.3 on a 1-5 Likert scale). Learning curves were established and distributed practice was found to be superior to massed practice, reported as mean end score (95% CI) of 15.7 (14.4-17.0) in distributed practice vs. 13.0 (11.9-14.1) with massed practice (P = .002). Simulator-integrated tutoring accelerated the initial performance, with mean score for tutored sessions of 14.6 (13.9-15.2) vs. 13.4 (12.8-14.0) for corresponding nontutored sessions (P < .01) but at the cost of a drop in performance once tutoring ceased. The performance drop was less with distributed practice, suggesting a protective effect when acquired skills were consolidated over time. The mean performance of the nontutored participants in the distributed practice group plateaued on a score of 16.0 (15.3-16.7) at approximately the ninth repetition, but the individual learning curves were highly variable. Novices can acquire basic mastoidectomy competencies with self-directed VR simulation training. Training should be organized with distributed practice, and simulator-integrated tutoring can be useful to accelerate the initial learning curve. Practice should be deliberate and toward a standard set level of proficiency that remains to be defined rather than toward the mean learning curve plateau.

Learning curves for single incision and conventional laparoscopic right hemicolectomy: a multidimensional analysis.

PubMed

Park, Yoonah; Yong, Yuen Geng; Yun, Seong Hyeon; Jung, Kyung Uk; Huh, Jung Wook; Cho, Yong Beom; Kim, Hee Cheol; Lee, Woo Yong; Chun, Ho-Kyung

2015-05-01

This study aimed to compare the learning curves and early postoperative outcomes for conventional laparoscopic (CL) and single incision laparoscopic (SIL) right hemicolectomy (RHC). This retrospective study included the initial 35 cases in each group. Learning curves were evaluated by the moving average of operative time, mean operative time of every five consecutive cases, and cumulative sum (CUSUM) analysis. The learning phase was considered overcome when the moving average of operative times reached a plateau, and when the mean operative time of every five consecutive cases reached a low point and subsequently did not vary by more than 30 minutes. Six patients with missing data in the CL RHC group were excluded from the analyses. According to the mean operative time of every five consecutive cases, learning phase of SIL and CL RHC was completed between 26 and 30 cases, and 16 and 20 cases, respectively. Moving average analysis revealed that approximately 31 (SIL) and 25 (CL) cases were needed to complete the learning phase, respectively. CUSUM analysis demonstrated that 10 (SIL) and two (CL) cases were required to reach a steady state of complication-free performance, respectively. Postoperative complications rate was higher in SIL than in CL group, but the difference was not statistically significant (17.1% vs. 3.4%). The learning phase of SIL RHC is longer than that of CL RHC. Early oncological outcomes of both techniques were comparable. However, SIL RHC had a statistically insignificant higher complication rate than CL RHC during the learning phase.

Modeling Creep Processes in Aging Polymers

NASA Astrophysics Data System (ADS)

Olali, N. V.; Voitovich, L. V.; Zazimko, N. N.; Malezhik, M. P.

2016-03-01

The photoelastic method is generalized to creep in hereditary aging materials. Optical-creep curves and mechanical-creep or optical-relaxation curves are used to interpret fringe patterns. For materials with constant Poisson's ratio, it is sufficient to use mechanical- or optical-creep curves for this purpose

Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions.

PubMed

Choi, Yoonha; Liu, Tiffany Ting; Pankratz, Daniel G; Colby, Thomas V; Barth, Neil M; Lynch, David A; Walsh, P Sean; Raghu, Ganesh; Kennedy, Giulia C; Huang, Jing

2018-05-09

We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects. We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~ 0.9 in cross-validation. Using in silico mixed samples in training, we prospectively defined a decision boundary to optimize specificity at ≥85%. The penalized logistic regression model showed greater reproducibility across technical replicates and was chosen as the final model. The final model showed sensitivity of 70% and specificity of 88% in the test set. We demonstrated that the suggested methodologies appropriately addressed challenges of the sample size, disease heterogeneity and technical batch effects and developed a highly accurate and robust classifier leveraging RNA sequencing for the classification of UIP.

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

PubMed

McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

2015-07-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning

PubMed Central

Bond, Krista M.; Taylor, Jordan A.

2015-01-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. PMID:26134640

Patterns in Teacher Learning in Different Phases of the Professional Career

ERIC Educational Resources Information Center

Vermunt, Jan D.; Endedijk, Maaike D.

2011-01-01

This paper reviews recent research on learning patterns of student teachers and experienced teachers, mostly in the context of educational innovation and teachers' professional development. The discussion is structured along a model of teacher learning patterns comprising learning activities, regulation of learning, beliefs on own learning about…

Gamma-Ray Light Curves from Pulsar Magnetospheres with Finite Conductivity

NASA Technical Reports Server (NTRS)

Harding, A. K.; Kalapotharakos, C.; Kazanas, D.; Contopoulos, I.

2012-01-01

The Fermi Large Area Telescope has provided an unprecedented database for pulsar emission studies that includes gamma-ray light curves for over 100 pulsars. Modeling these light curves can reveal and constrain the geometry of the particle accelerator, as well as the pulsar magnetic field structure. We have constructed 3D magnetosphere models with finite conductivity, that bridge the extreme vacuum and force-free solutions used in previous light curves modeling. We are investigating the shapes of pulsar gamma-ray light curves using these dissipative solutions with two different approaches: (l) assuming geometric emission patterns of the slot gap and outer gap, and (2) using the parallel electric field provided by the resistive models to compute the trajectories and . emission of the radiating particles. The light curves using geometric emission patterns show a systematic increase in gamma-ray peak phase with increasing conductivity, introducing a new diagnostic of these solutions. The light curves using the model electric fields are very sensitive to the conductivity but do not resemble the observed Fermi light curves, suggesting that some screening of the parallel electric field, by pair cascades not included in the models, is necessary

Searching for exoplanets using artificial intelligence

NASA Astrophysics Data System (ADS)

Pearson, Kyle A.; Palafox, Leon; Griffith, Caitlin A.

2018-02-01

In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects which, unlike current methods uses a neural network. Neural networks, also called "deep learning" or "deep nets" are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time-series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.

Toucan hand feeding and nestling growth.

PubMed

St Leger, Judy; Vince, Martin; Jennings, Jerry; McKerney, Erin; Nilson, Erika

2012-05-01

A retrospective analysis of hand-feeding records and growth data from 3 facilities was performed to determine the growth pattern for 8 toucan species raised in captivity. General philosophies of breeding and rearing were similar but approaches to hand-feeding varied. General hand-feeding and chick management records from hatch to fledging were reviewed for 2 of the 3 facilities. Effective hand-feeding formulas were commercially available and minimally modified. Growth curves were developed. Curves approximated typical expected patterns of nestling growth with no loss of weight at fledging. This study provides a basis for hand-feeding protocols and growth curves to assess development.

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

DTIC Science & Technology

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

A Learning Patterns Perspective on Student Learning in Higher Education: State of the Art and Moving Forward

ERIC Educational Resources Information Center

Vermunt, Jan D.; Donche, Vincent

2017-01-01

The aim of this article is to review the state of the art of research and theory development on student learning patterns in higher education and beyond. First, the learning patterns perspective and the theoretical framework are introduced. Second, research published since 2004 on student learning patterns is systematically identified and…

Site index curves for black, white, scarlet, and chestnut oaks in the Central States.

Treesearch

Willard H. Carmean

1971-01-01

Stem analyses showed polymorphic patterns of height growth for each species and for different levels of site quality. New site index curves are presented that show better height growth in later years than predicted by older harmonized site index curves.

Predicting Robust Learning with the Visual Form of the Moment-by-Moment Learning Curve

ERIC Educational Resources Information Center

Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M.

2013-01-01

We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…

Undergraduate Student Self-Efficacy and Perceptions of Virtual World Learning Experience

ERIC Educational Resources Information Center

Stanton, Lorraine May

2017-01-01

Virtual worlds are innovative teaching and learning methods that can provide immersive and engaging learning experiences (Lu, 2010). Though they have potential benefits, students sometimes experience a steep learning curve and discomfort with the technology (Warburton, 2009). This study explored how students in two American Studies classes using…

Individual Differences in a Positional Learning Task across the Adult Lifespan

ERIC Educational Resources Information Center

Rast, Philippe; Zimprich, Daniel

2010-01-01

This study aimed at modeling individual and average non-linear trajectories of positional learning using a structured latent growth curve approach. The model is based on an exponential function which encompasses three parameters: Initial performance, learning rate, and asymptotic performance. These learning parameters were compared in a positional…

An experimental approach to non - extensive statistical physics and Epidemic Type Aftershock Sequence (ETAS) modeling. The case of triaxially deformed sandstones using acoustic emissions.

NASA Astrophysics Data System (ADS)

Stavrianaki, K.; Vallianatos, F.; Sammonds, P. R.; Ross, G. J.

2014-12-01

Fracturing is the most prevalent deformation mechanism in rocks deformed in the laboratory under simulated upper crustal conditions. Fracturing produces acoustic emissions (AE) at the laboratory scale and earthquakes on a crustal scale. The AE technique provides a means to analyse microcracking activity inside the rock volume and since experiments can be performed under confining pressure to simulate depth of burial, AE can be used as a proxy for natural processes such as earthquakes. Experimental rock deformation provides us with several ways to investigate time-dependent brittle deformation. Two main types of experiments can be distinguished: (1) "constant strain rate" experiments in which stress varies as a result of deformation, and (2) "creep" experiments in which deformation and deformation rate vary over time as a result of an imposed constant stress. We conducted constant strain rate experiments on air-dried Darley Dale sandstone samples in a variety of confining pressures (30MPa, 50MPa, 80MPa) and in water saturated samples with 20 MPa initial pore fluid pressure. The results from these experiments used to determine the initial loading in the creep experiments. Non-extensive statistical physics approach was applied to the AE data in order to investigate the spatio-temporal pattern of cracks close to failure. A more detailed study was performed for the data from the creep experiments. When axial stress is plotted against time we obtain the trimodal creep curve. Calculation of Tsallis entropic index q is performed to each stage of the curve and the results are compared with the ones from the constant strain rate experiments. The Epidemic Type Aftershock Sequence model (ETAS) is also applied to each stage of the creep curve and the ETAS parameters are calculated. We investigate whether these parameters are constant across all stages of the curve, or whether there are interesting patterns of variation. This research has been co-funded by the European Union (European Social Fund) and Greek national resources under the framework of the "THALES Program: SEISMO FEAR HELLARC" project of the "Education & Lifelong Learning" Operational Programme.

The learning curve of laparoendoscopic single-site (LESS) cholecystectomy: definable, short, and safe.

PubMed

Hernandez, Jonathan; Ross, Sharona; Morton, Connor; McFarlin, Kellie; Dahal, Sujat; Golkar, Farhaad; Albrink, Michael; Rosemurgy, Alexander

2010-11-01

The applications of laparoendoscopic single-site (LESS) surgery, including cholecystectomy, are occurring quickly, although little is generally known about issues associated with the learning curve of this new technique including operative time, conversion rates, and safety. We prospectively followed all patients undergoing LESS cholecystectomy, and compared operations undertaken at our institutions in cohorts of 25 patients with respect to operative times, conversion rates, and complications. One-hundred fifty patients of mean age 46 years underwent LESS cholecystectomy. No significant differences in operative times were demonstrable between any of the 25-patient cohorts operated on at our institution. A significant reduction in operative times (p < 0.001) after completion of 75 LESS procedures was, however, identified with the experience of a single surgeon. No significant reduction in the number of procedures requiring an additional trocar(s) or conversion to open operations was observed after completion of 25 LESS cholecystectomies. Complication rates were low, and not significantly different between any 25-patient cohorts. For surgeons proficient with multi-incision laparoscopic cholecystectomy, the learning curve for LESS cholecystectomy begins near proficiency. Operative complications and conversions were infrequent and unchanged across successive 25-patient cohorts, and were similar to those reported for multi-incision laparoscopic cholecystectomy after the learning curve. Copyright © 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

Lumpy Demand and the Diagrammatics of Aggregation.

ERIC Educational Resources Information Center

Shmanske, Stephen; Packey, Daniel

1999-01-01

Illustrates how a simple discontinuity in an individual's demand curve, or inverse-demand curve, affects the shape of market aggregate curves. Shows, for private goods, that an infinitesimal change in quantity can lead to large changes in consumption patterns; for collective goods, the analysis suggests a theory of coalition building. (DSK)

Nonlinear Growth Models in M"plus" and SAS

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam

2009-01-01

Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the M"plus" structural modeling program and the nonlinear…

Utility of Interobserver Agreement Statistics in Establishing Radiology Resident Learning Curves During Self-directed Radiologic Anatomy Training.

PubMed

Tureli, Derya; Altas, Hilal; Cengic, Ismet; Ekinci, Gazanfer; Baltacioglu, Feyyaz

2015-10-01

The aim of the study was to ascertain the learning curves for the radiology residents when first introduced to an anatomic structure in magnetic resonance images (MRI) to which they have not been previously exposed to. The iliolumbar ligament is a good marker for testing learning curves of radiology residents because the ligament is not part of a routine lumbar MRI reporting and has high variability in detection. Four radiologists, three residents without previous training and one mentor, studied standard axial T1- and T2-weighted images of routine lumbar MRI examinations. Radiologists had to define iliolumbar ligament while blinded to each other's findings. Interobserver agreement analyses, namely Cohen and Fleiss κ statistics, were performed for groups of 20 cases to evaluate the self-learning curve of radiology residents. Mean κ values of resident-mentor pairs were 0.431, 0.608, 0.604, 0.826, and 0.963 in the analysis of successive groups (P < .001). The results indicate that the concordance between the experienced and inexperienced radiologists started as weak (κ <0.5) and gradually became very acceptable (κ >0.8). Therefore, a junior radiology resident can obtain enough experience in identifying a rather ambiguous anatomic structure in routine MRI after a brief instruction of a few minutes by a mentor and studying approximately 80 cases by oneself. Implementing this methodology will help radiology educators obtain more concrete ideas on the optimal time and effort required for supported self-directed visual learning processes in resident education. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Colorectal endoscopic submucosal dissection (ESD) in the West - when can satisfactory results be obtained? A single-operator learning curve analysis.

PubMed

Spychalski, Michał; Skulimowski, Aleksander; Dziki, Adam; Saito, Yutaka

2017-12-01

Up to date we lack a detailed description of the colorectal endoscopic submucosal dissection (ESD) learning curve, that would represent the experience of the Western center. The aim of this study was to define the critical points of the learning curve and to draw up lesions qualification guidelines tailored to the endoscopists experience. We have carried out a single center prospective study. Between June 2013 and December 2016, 228 primary colorectal lesions were managed by ESD procedure. In order to create a learning curve model and to carry out the analysis the cases were divided into six periods, each consisting of 38 cases. The overall en bloc resection rate was 79.39%. The lowest en bloc resection rate (52.36%) was observed in the first period. After completing 76 procedures, the resection rate surged to 86% and it was accompanied by the significant increase in the mean procedure speed of ≥9 cm 2 /h. Lesions localization and diameter had a signification impact on the outcomes. After 76 procedures, en bloc resection rate of 90.9 and 90.67% were achieved for the left side of colon and rectum, respectively. In the right side of colon statistically significant lower resection rate of 67.57% was observed. We have proved that in the setting of the Western center, colorectal ESD can yield excellent results. It seems that the key to the success during the learning period is 'tailoring' lesions qualification guidelines to the experience of the endoscopist, as lesions diameter and localization highly influence the outcomes.

Laparoscopic recurrent inguinal hernia repair during the learning curve: it can be done?

PubMed

Bracale, Umberto; Sciuto, Antonio; Andreuccetti, Jacopo; Merola, Giovanni; Pecchia, Leandro; Melillo, Paolo; Pignata, Giusto

2017-01-01

Trans-Abdominal Preperitoneal Patch (TAPP) repairs for Recurrent Hernia (RH) is a technically demanding procedure. It has to be performed only by surgeons with extensive experience in the laparoscopic approach. The purpose of this study is to evaluate the surgical safety and the efficacy of TAPP for RH performed in a tutoring program by surgeons in practice (SP). All TAPP repairs for RH performed by the same surgical team have been included in the study. We have evaluated the results of three SP during their learning curve in a tutoring program. Then these results have been compared to those of a highly experienced laparoscopic surgeon (Benchmark). A total of 530 TAPP repairs have been performed. Among these, 83 TAPP have been executed for RH, of which 43 by the Benchmark and 40 by the SP. When we have compared the outcomes of the Benchmark with those of SP, no significant difference has been observed about morbidity and recurrence while the operative time has been significantly longer for the SP. No intraoperative complications have occurred. International guidelines urge that TAPP repair for RH has to be performed only by surgeons with extensive experience in the laparoscopic approach. The results of the present study demonstrate that TAPP for RH could be performed also by surgeons in training during a learning program. We retain that an adequate tutoring program could lead a surgeon in practice to perform more complex hernia procedures without jeopardizing patient safety throughout the learning curve period. Laparoscopy, Learning Curve, Recurrent Hernia.

Site index curves for northern hardwoods in northern Wisconsin and Upper Michigan.

Treesearch

Willard H. Carmean

1978-01-01

Site index curves based on stem analyses were computed for 13 species found in even-aged, second growth northern hardwood stands. These curves showed that most species had similarly-shaped height growth curves in early years, but after 40 years differences in both rate and pattern of growth between species was evident for trees growing on medium and good sites. Most...

Wrinkling crystallography on spherical surfaces

PubMed Central

Brojan, Miha; Terwagne, Denis; Lagrange, Romain; Reis, Pedro M.

2015-01-01

We present the results of an experimental investigation on the crystallography of the dimpled patterns obtained through wrinkling of a curved elastic system. Our macroscopic samples comprise a thin hemispherical shell bound to an equally curved compliant substrate. Under compression, a crystalline pattern of dimples self-organizes on the surface of the shell. Stresses are relaxed by both out-of-surface buckling and the emergence of defects in the quasi-hexagonal pattern. Three-dimensional scanning is used to digitize the topography. Regarding the dimples as point-like packing units produces spherical Voronoi tessellations with cells that are polydisperse and distorted, away from their regular shapes. We analyze the structure of crystalline defects, as a function of system size. Disclinations are observed and, above a threshold value, dislocations proliferate rapidly with system size. Our samples exhibit striking similarities with other curved crystals of charged particles and colloids. Differences are also found and attributed to the far-from-equilibrium nature of our patterns due to the random and initially frozen material imperfections which act as nucleation points, the presence of a physical boundary which represents an additional source of stress, and the inability of dimples to rearrange during crystallization. Even if we do not have access to the exact form of the interdimple interaction, our experiments suggest a broader generality of previous results of curved crystallography and their robustness on the details of the interaction potential. Furthermore, our findings open the door to future studies on curved crystals far from equilibrium. PMID:25535355

Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks

PubMed Central

Brosch, Tobias; Neumann, Heiko; Roelfsema, Pieter R.

2015-01-01

The processing of a visual stimulus can be subdivided into a number of stages. Upon stimulus presentation there is an early phase of feedforward processing where the visual information is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This is followed by a later phase where horizontal connections within areas and feedback connections from higher areas back to lower areas come into play. In this later phase, image elements that are behaviorally relevant are grouped by Gestalt grouping rules and are labeled in the cortex with enhanced neuronal activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mechanisms for reward-based learning of new grouping rules. We derive a learning rule that can explain how rewards influence the information flow through feedforward, horizontal and feedback connections. We illustrate the efficiency with two tasks that have been used to study the neuronal correlates of perceptual organization in early visual cortex. The first task is called contour-integration and demands the integration of collinear contour elements into an elongated curve. We show how reward-based learning causes an enhancement of the representation of the to-be-grouped elements at early levels of a recurrent neural network, just as is observed in the visual cortex of monkeys. The second task is curve-tracing where the aim is to determine the endpoint of an elongated curve composed of connected image elements. If trained with the new learning rule, neural networks learn to propagate enhanced activity over the curve, in accordance with neurophysiological data. We close the paper with a number of model predictions that can be tested in future neurophysiological and computational studies. PMID:26496502

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

PubMed

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Technical refinement and learning curve for attenuating neurapraxia during robotic-assisted radical prostatectomy to improve sexual function.

PubMed

Alemozaffar, Mehrdad; Duclos, Antoine; Hevelone, Nathanael D; Lipsitz, Stuart R; Borza, Tudor; Yu, Hua-Yin; Kowalczyk, Keith J; Hu, Jim C

2012-06-01

While radical prostatectomy surgeon learning curves have characterized less blood loss, shorter operative times, and fewer positive margins, there is a dearth of studies characterizing learning curves for improving sexual function. Additionally, while learning curve studies often define volume thresholds for improvement, few of these studies demonstrate specific technical modifications that allow reproducibility of improved outcomes. Demonstrate and quantify the learning curve for improving sexual function outcomes based on technical refinements that reduce neurovascular bundle displacement during nerve-sparing robot-assisted radical prostatectomy (RARP). We performed a retrospective study of 400 consecutive RARPs, categorized into groups of 50, performed after elimination of continuous surgeon/assistant neurovascular bundle countertraction. Our approach to RARP has been described previously. A single-console robotic system was used for all cases. Expanded Prostate Cancer Index Composite sexual function was measured within 1 yr of RARP. Linear regression was performed to determine factors influencing the recovery of sexual function. Greater surgeon experience was associated with better 5-mo sexual function (p = 0.007) and a trend for better 12-mo sexual function (p = 0.061), with improvement plateauing after 250-300 cases. Additionally, younger patient age (both p<0.02) and better preoperative sexual function (<0.001) were associated with better 5- and 12-mo sexual function. Moreover, trainee robotic console time during nerve sparing was associated with worse 12-mo sexual function (p=0.021), while unilateral nerve sparing/non-nerve sparing was associated with worse 5-mo sexual function (p = 0.009). Limitations include the retrospective single-surgeon design. With greater surgeon experience, attenuating lateral displacement of the neurovascular bundle and resultant neurapraxia improve postoperative sexual function. However, to maximize outcomes, appropriate patient selection must be exercised when allowing trainee nerve-sparing involvement. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Simultaneous development of laparoscopy and robotics provides acceptable perioperative outcomes and shows robotics to have a faster learning curve and to be overall faster in rectal cancer surgery: analysis of novice MIS surgeon learning curves.

PubMed

Melich, George; Hong, Young Ki; Kim, Jieun; Hur, Hyuk; Baik, Seung Hyuk; Kim, Nam Kyu; Sender Liberman, A; Min, Byung Soh

2015-03-01

Laparoscopy offers some evidence of benefit compared to open rectal surgery. Robotic rectal surgery is evolving into an accepted approach. The objective was to analyze and compare laparoscopic and robotic rectal surgery learning curves with respect to operative times and perioperative outcomes for a novice minimally invasive colorectal surgeon. One hundred and six laparoscopic and 92 robotic LAR rectal surgery cases were analyzed. All surgeries were performed by a surgeon who was primarily trained in open rectal surgery. Patient characteristics and perioperative outcomes were analyzed. Operative time and CUSUM plots were used for evaluating the learning curve for laparoscopic versus robotic LAR. Laparoscopic versus robotic LAR outcomes feature initial group operative times of 308 (291-325) min versus 397 (373-420) min and last group times of 220 (212-229) min versus 204 (196-211) min-reversed in favor of robotics; major complications of 4.7 versus 6.5 % (NS), resection margin involvement of 2.8 versus 4.4 % (NS), conversion rate of 3.8 versus 1.1 (NS), lymph node harvest of 16.3 versus 17.2 (NS), and estimated blood loss of 231 versus 201 cc (NS). Due to faster learning curves for extracorporeal phase and total mesorectal excision phase, the robotic surgery was observed to be faster than laparoscopic surgery after the initial 41 cases. CUSUM plots demonstrate acceptable perioperative surgical outcomes from the beginning of the study. Initial robotic operative times improved with practice rapidly and eventually became faster than those for laparoscopy. Developing both laparoscopic and robotic skills simultaneously can provide acceptable perioperative outcomes in rectal surgery. It might be suggested that in the current milieu of clashing interests between evolving technology and economic constrains, there might be advantages in embracing both approaches.

The learning curve of laparoscopic liver resection after the Louisville statement 2008: Will it be more effective and smooth?

PubMed

Lin, Chung-Wei; Tsai, Tzu-Jung; Cheng, Tsung-Yen; Wei, Hung-Kuang; Hung, Chen-Fang; Chen, Yin-Yin; Chen, Chii-Ming

2016-07-01

Laparoscopic liver resection (LLR) has been proven to be feasible and safe. However, it is a difficult and complex procedure with a steep learning curve. The aim of this study was to evaluate the learning curve of LLR at our institutions since 2008. One hundred and twenty-six consecutive LLRs were included from May 2008 to December 2014. Patient characteristics, operative data, and surgical outcomes were collected prospectively and analyzed. The median tumor size was 25 mm (range 5-90 mm), and 96 % of the resected tumors were malignant. 41.3 % (52/126) of patients had pathologically proven liver cirrhosis. The median operation time was 216 min (range 40-602 min) with a median blood loss of 100 ml (range 20-2300 ml). The median length of hospital stay was 4 days (range 2-10 days). Six major postoperative complications occurred in this series, and there was no 90-day postoperative mortality. Regarding the incidence of major operative events including operation time longer than 300 min, perioperative blood loss above 500 ml, and major postoperative complications, the learning curve [as evaluated by the cumulative sum (CUSUM) technique] showed its first reverse after 22 cases. The indication of laparoscopic resection in this series extended after 60 cases to include tumors located in difficult locations (segments 4a, 7, 8) and major hepatectomy. CUSUM showed that the incidence of major operative events proceeded to increase again, and the second reverse was noted after an additional 40 cases of experience. Location of the tumor in a difficult area emerged as a significant predictor of major operative events. In carefully selected patients, CUSUM analysis showed 22 cases were needed to overcome the learning curve for minor LLR.

Gait patterns for crime fighting: statistical evaluation

NASA Astrophysics Data System (ADS)

Sulovská, Kateřina; Bělašková, Silvie; Adámek, Milan

2013-10-01

The criminality is omnipresent during the human history. Modern technology brings novel opportunities for identification of a perpetrator. One of these opportunities is an analysis of video recordings, which may be taken during the crime itself or before/after the crime. The video analysis can be classed as identification analyses, respectively identification of a person via externals. The bipedal locomotion focuses on human movement on the basis of their anatomical-physiological features. Nowadays, the human gait is tested by many laboratories to learn whether the identification via bipedal locomotion is possible or not. The aim of our study is to use 2D components out of 3D data from the VICON Mocap system for deep statistical analyses. This paper introduces recent results of a fundamental study focused on various gait patterns during different conditions. The study contains data from 12 participants. Curves obtained from these measurements were sorted, averaged and statistically tested to estimate the stability and distinctiveness of this biometrics. Results show satisfactory distinctness of some chosen points, while some do not embody significant difference. However, results presented in this paper are of initial phase of further deeper and more exacting analyses of gait patterns under different conditions.

A study of active learning methods for named entity recognition in clinical text.

PubMed

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random sampling, the best uncertainty based method saved 42% annotations in words. But the best diversity based method reduced only 7% annotation effort. In the simulated setting, AL methods, particularly uncertainty-sampling based approaches, seemed to significantly save annotation cost for the clinical NER task. The actual benefit of active learning in clinical NER should be further evaluated in a real-time setting. Copyright © 2015 Elsevier Inc. All rights reserved.

Using a high-fidelity patient simulator with first-year medical students to facilitate learning of cardiovascular function curves.

PubMed

Harris, David M; Ryan, Kathleen; Rabuck, Cynthia

2012-09-01

Students are relying on technology for learning more than ever, and educators need to adapt to facilitate student learning. High-fidelity patient simulators (HFPS) are usually reserved for the clinical years of medical education and are geared to improve clinical decision skills, teamwork, and patient safety. Finding ways to incorporate HFPS into preclinical medical education represents more of a challenge, and there is limited literature regarding its implementation. The main objective of this study was to implement a HFPS activity into a problem-based curriculum to enhance the learning of basic sciences. More specifically, the focus was to aid in student learning of cardiovascular function curves and help students develop heart failure treatment strategies based on basic cardiovascular physiology concepts. Pretests and posttests, along with student surveys, were used to determine student knowledge and perception of learning in two first-year medical school classes. There was an increase of 21% and 22% in the percentage of students achieving correct answers on a posttest compared with their pretest score. The median number of correct questions increased from pretest scores of 2 and 2.5 to posttest scores of 4 and 5 of a possible total of 6 in each respective year. Student survey data showed agreement that the activity aided in learning. This study suggests that a HFPS activity can be implemented during the preclinical years of medical education to address basic science concepts. Additionally, it suggests that student learning of cardiovascular function curves and heart failure strategies are facilitated.

Learning curves for single incision and conventional laparoscopic right hemicolectomy: a multidimensional analysis

PubMed Central

Park, Yoonah; Yong, Yuen Geng; Jung, Kyung Uk; Huh, Jung Wook; Cho, Yong Beom; Kim, Hee Cheol; Lee, Woo Yong; Chun, Ho-Kyung

2015-01-01

Purpose This study aimed to compare the learning curves and early postoperative outcomes for conventional laparoscopic (CL) and single incision laparoscopic (SIL) right hemicolectomy (RHC). Methods This retrospective study included the initial 35 cases in each group. Learning curves were evaluated by the moving average of operative time, mean operative time of every five consecutive cases, and cumulative sum (CUSUM) analysis. The learning phase was considered overcome when the moving average of operative times reached a plateau, and when the mean operative time of every five consecutive cases reached a low point and subsequently did not vary by more than 30 minutes. Results Six patients with missing data in the CL RHC group were excluded from the analyses. According to the mean operative time of every five consecutive cases, learning phase of SIL and CL RHC was completed between 26 and 30 cases, and 16 and 20 cases, respectively. Moving average analysis revealed that approximately 31 (SIL) and 25 (CL) cases were needed to complete the learning phase, respectively. CUSUM analysis demonstrated that 10 (SIL) and two (CL) cases were required to reach a steady state of complication-free performance, respectively. Postoperative complications rate was higher in SIL than in CL group, but the difference was not statistically significant (17.1% vs. 3.4%). Conclusion The learning phase of SIL RHC is longer than that of CL RHC. Early oncological outcomes of both techniques were comparable. However, SIL RHC had a statistically insignificant higher complication rate than CL RHC during the learning phase. PMID:25960990

V1 orientation plasticity is explained by broadly tuned feedforward inputs and intracortical sharpening.

PubMed

Teich, Andrew F; Qian, Ning

2010-03-01

Orientation adaptation and perceptual learning change orientation tuning curves of V1 cells. Adaptation shifts tuning curve peaks away from the adapted orientation, reduces tuning curve slopes near the adapted orientation, and increases the responses on the far flank of tuning curves. Learning an orientation discrimination task increases tuning curve slopes near the trained orientation. These changes have been explained previously in a recurrent model (RM) of orientation selectivity. However, the RM generates only complex cells when they are well tuned, so that there is currently no model of orientation plasticity for simple cells. In addition, some feedforward models, such as the modified feedforward model (MFM), also contain recurrent cortical excitation, and it is unknown whether they can explain plasticity. Here, we compare plasticity in the MFM, which simulates simple cells, and a recent modification of the RM (MRM), which displays a continuum of simple-to-complex characteristics. Both pre- and postsynaptic-based modifications of the recurrent and feedforward connections in the models are investigated. The MRM can account for all the learning- and adaptation-induced plasticity, for both simple and complex cells, while the MFM cannot. The key features from the MRM required for explaining plasticity are broadly tuned feedforward inputs and sharpening by a Mexican hat intracortical interaction profile. The mere presence of recurrent cortical interactions in feedforward models like the MFM is insufficient; such models have more rigid tuning curves. We predict that the plastic properties must be absent for cells whose orientation tuning arises from a feedforward mechanism.

Radiomics-based features for pattern recognition of lung cancer histopathology and metastases.

PubMed

Ferreira Junior, José Raniery; Koenigkam-Santos, Marcel; Cipriano, Federico Enrique Garcia; Fabro, Alexandre Todorovic; Azevedo-Marques, Paulo Mazzoncini de

2018-06-01

lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models. local image datasets of confirmed primary malignant pulmonary tumors were retrospectively evaluated for testing and validation. CT images acquired with same protocol were semiautomatically segmented. Tumors were characterized by clinical features and computer attributes of intensity, histogram, texture, shape, and volume. Three machine learning classifiers used up to 100 selected features to perform the analysis. radiomics-based features yielded areas under the receiver operating characteristic curve of 0.89, 0.97, and 0.92 at testing and 0.75, 0.71, and 0.81 at validation for lymph nodal metastasis, distant metastasis, and histopathology pattern recognition, respectively. the radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning. Copyright © 2018 Elsevier B.V. All rights reserved.

A strategic systems perspective of organizational learning theory: models for a case study at the Jet Propulsion Laboratory

NASA Technical Reports Server (NTRS)

Neece, O.

2000-01-01

Organizational learning is an umbrella term that covers a variety of topics including; learning curves, productivity, organizational memory, organizational forgetting, knowledge transfer, knowledge sharing and knowledge creation. This treatise will review some of these theories in concert with a model of how organizations learn.

The Role of Cognitive Abilities in Laparoscopic Simulator Training

ERIC Educational Resources Information Center

Groenier, M.; Schraagen, J. M. C.; Miedema, H. A. T.; Broeders, I. A. J. M.

2014-01-01

Learning minimally invasive surgery (MIS) differs substantially from learning open surgery and trainees differ in their ability to learn MIS. Previous studies mainly focused on the role of visuo-spatial ability (VSA) on the learning curve for MIS. In the current study, the relationship between spatial memory, perceptual speed, and general…

Concentrated photovoltaics system costs and learning curve analysis

NASA Astrophysics Data System (ADS)

Haysom, Joan E.; Jafarieh, Omid; Anis, Hanan; Hinzer, Karin

2013-09-01

An extensive set of costs in /W for the installed costs of CPV systems has been amassed from a range of public sources, including both individual company prices and market reports. Cost reductions over time are very evident, with current prices for 2012 in the range of 3.0 ± 0.7 /W and a predicted cost of 1.5 /W for 2020. Cost data is combined with deployment volumes in a learning curve analysis, providing a fitted learning rate of either 18.5% or 22.3% depending on the methodology. This learning rate is compared to that of PV modules and PV installed systems, and the influence of soft costs is discussed. Finally, if an annual growth rate of 39% is assumed for deployed volumes, then, using the learning rate of 20%, this would predict the achievement of a cost point of 1.5 /W by 2016.

A randomized control trial to evaluate the importance of pre-training basic laparoscopic psychomotor skills upon the learning curve of laparoscopic intra-corporeal knot tying.

PubMed

Molinas, Carlos Roger; Binda, Maria Mercedes; Sisa, Cesar Manuel; Campo, Rudi

2017-01-01

Training of basic laparoscopic psychomotor skills improves the acquisition of more advanced laparoscopic tasks, such as laparoscopic intra-corporeal knot tying (LICK). This randomized controlled trial was designed to evaluate whether pre-training of basic skills, as laparoscopic camera navigation (LCN), hand-eye coordination (HEC), and bimanual coordination (BMC), and the combination of the three of them, has any beneficial effect upon the learning curve of LICK. The study was carried out in a private center in Asunción, Paraguay, by 80 medical students without any experience in surgery. Four laparoscopic tasks were performed in the ENCILAP model (LCN, HEC, BMC, and LICK). Participants were allocated to 5 groups (G1-G5). The study was structured in 5 phases. In phase 1, they underwent a base-line test ( T 1 ) for all tasks (1 repetition of each task in consecutive order). In phase 2, participants underwent different training programs (30 consecutive repetitions) for basic tasks according to the group they belong to (G1: none; G2: LCN; G3: HEC; G4: BMC; and G5: LCN, HEC, and BMC). In phase 3, they were tested again ( T 2 ) in the same manner than at T 1 . In phase 4, they underwent a standardized training program for LICK (30 consecutive repetitions). In phase 5, they were tested again ( T 3 ) in the same manner than at T 1 and T 2 . At each repetition, scoring was based on the time taken for task completion system. The scores were plotted and non-linear regression models were used to fit the learning curves to one- and two-phase exponential decay models for each participant (individual curves) and for each group (group curves). The LICK group learning curves fitted better to the two-phase exponential decay model. From these curves, the starting points ( Y 0), the point after HEC training/before LICK training ( Y 1), the Plateau, and the rate constants ( K ) were calculated. All groups, except for G4, started from a similar point ( Y 0). At Y 1, G5 scored already better than the others (G1 p  = .004; G2 p  = .04; G3 p  < .0001; G4 NS). Although all groups reached a similar Plateau, G5 has a quicker learning than the others, demonstrated by a higher K (G1 p  < 0.0001; G2 p  < 0.0001; G3 p  < 0.0001; and G4 p  < 0.0001). Our data confirms that training improves laparoscopic skills and demonstrates that pre-training of all basic skills (i.e., LCN, HEC, and BMC) shortens the LICK learning curve.

Transition Behaviors of Configurations of Colloidal Particles at a Curved Oil-Water Interface

PubMed Central

Lee, Mina; Xia, Ming; Park, Bum Jun

2016-01-01

We studied the transition behaviors of colloidal arrangements confined at a centro-symmetrically curved oil-water interface. We found that assemblies composed of several colloidal particles at the curved interface exhibit at least two unique patterns that can be attributed to two factors: heterogeneity of single-colloid self-potential and assembly kinetics. The presence of the two assembly structures indicates that an essential energy barrier between the two structures exists and that one of the structures is kinetically stable. This energy barrier can be overcome via external stimuli (e.g., convection and an optical force), leading to dynamic transitions of the assembly patterns. PMID:28773263

Comparison of the scoliosis curve patterns and MRI syrinx cord characteristics of idiopathic syringomyelia versus Chiari I malformation.

PubMed

Zhu, Zezhang; Sha, Shifu; Chu, Winnie C C; Yan, Huang; Xie, Dingding; Liu, Zhen; Sun, Xu; Zhu, Weiguo; Cheng, Jack C Y; Qiu, Yong

2016-02-01

Although the more readily available MR imaging has brought about more incidental findings of idiopathic syringomyelia (IS), no published study has specifically addressed the clinical and imaging features of IS-associated scoliosis. Since IS and Chiari I malformation (CMI)-type syringomyelia are hypothesized to share a common underlying developmental pathomechanism, this study aimed to investigate the scoliosis curve patterns and MRI syrinx cord characteristics of patients with IS comparing with those seen in CMI. Sixty-one patients with scoliosis secondary to IS were identified and reviewed retrospectively. The curve pattern and specific curve features were recorded and compared with historic CMI controls. Location, size, and morphological appearance of the syrinx were systematically assessed on MR images. The maximal syrinx/cord ratio and rostrocaudal length of the syrinx in IS averaged 0.43 ± 0.16 (range 0.17-0.78) and 4.6 ± 2.5 (range 2-15) vertebral levels, respectively, both of which were smaller than those reported in CMI-type syringomyelia. Regarding the characteristics of IS-related scoliosis, sagittal profiles as well as the frequency of curve patterns and atypical features were all found to resemble those in patients with CMI (P > .05). Among the 47 individuals with a single thoracic curve, Fisher exact test revealed a significant correlation between curve convexity and the dominant side of deviated syrinx (83.3 % concordance rate, P = .021). In addition, apex of the thoracic curve trended toward being significantly correlated with the level of maximum expansion of the syrinx (P = .066). Radiological characteristics of scoliosis were found to be similar between idiopathic and CMI-type syrinx in both the coronal and sagittal planes, adding further evidence to the concept that these entities may be part of a spectrum of disease sharing a common pathophysiological mechanism. The thoracic spine in IS patients tended to be convex to the deviated side of syrinx, which indirectly supported the likely role of spinal cord dysfunction in the pathogenesis of syrinx-associated spinal deformities.

Estimation of median growth curves for children up two years old based on biresponse local linear estimator

NASA Astrophysics Data System (ADS)

Chamidah, Nur; Rifada, Marisa

2016-03-01

There is significant of the coeficient correlation between weight and height of the children. Therefore, the simultaneous model estimation is better than partial single response approach. In this study we investigate the pattern of sex difference in growth curve of children from birth up to two years of age in Surabaya, Indonesia based on biresponse model. The data was collected in a longitudinal representative sample of the Surabaya population of healthy children that consists of two response variables i.e. weight (kg) and height (cm). While a predictor variable is age (month). Based on generalized cross validation criterion, the modeling result based on biresponse model by using local linear estimator for boy and girl growth curve gives optimal bandwidth i.e 1.41 and 1.56 and the determination coefficient (R2) i.e. 99.99% and 99.98%,.respectively. Both boy and girl curves satisfy the goodness of fit criterion i.e..the determination coefficient tends to one. Also, there is difference pattern of growth curve between boy and girl. The boy median growth curves is higher than those of girl curve.

Doctoral Student Learning Patterns: Learning about Active Knowledge Creation or Passive Production

ERIC Educational Resources Information Center

Vekkaila, Jenna; Pyhältö, Kirsi

2016-01-01

Doctoral studies are about learning to create new knowledge and to become a researcher. Yet surprisingly little is known about the individual learning patterns of doctoral students. The study aims to explore learning patterns among natural science doctoral students. The participants included 19 doctoral students from a top-level natural science…

Deriving Process-Driven Collaborative Editing Pattern from Collaborative Learning Flow Patterns

ERIC Educational Resources Information Center

Marjanovic, Olivera; Skaf-Molli, Hala; Molli, Pascal; Godart, Claude

2007-01-01

Collaborative Learning Flow Patterns (CLFPs) have recently emerged as a new method to formulate best practices in structuring the flow of activities within various collaborative learning scenarios. The term "learning flow" is used to describe coordination and sequencing of learning tasks. This paper adopts the existing concept of CLFP and argues…

A comparative rugoscopic study of the dentate and edentulous individuals in the South Indian population.

PubMed

Rajguru, Jagdish Prasad; Misra, Satya Ranjan; Somayaji, Nagaveni S; Masthan, K M K; Babu, Aravindha N; Mohanty, Neeta

2014-01-01

This study analyzes the rugae pattern in dentulous and edentulous patients and also evaluates the association of rugae pattern between males and females. This study aims to investigate rugae patterns in dentulous and edentulous patients of both sexes in South Indian population and to find whether palatoscopy is a useful tool in human identification. Four hundred outpatients from Sree Balaji Dental College and Hospital, Chennai, were included in the study. The study group was equally divided between the sexes, which was further categorized into 100 dentulous and edentulous patients, respectively. The edentulous male showed the highest mean of wavy pattern and total absence of circular pattern while the edentulous female group showed the highest mean of curved pattern and total absence of nonspecific pattern, while dentate population showed similar value as that of the overall population such as straight, wavy, and curved patterns. The present study concludes that there is similar rugae pattern of distribution between male and female dentate population while there is varied pattern between the sexes of edentulous population. However, the most predominant patterns were straight, wavy, and circular patterns.

Precision Learning Assessment: An Alternative to Traditional Assessment Techniques.

ERIC Educational Resources Information Center

Caltagirone, Paul J.; Glover, Christopher E.

1985-01-01

A continuous and curriculum-based assessment method, Precision Learning Assessment (PLA), which integrates precision teaching and norm-referenced techniques, was applied to a math computation curriculum for 214 third graders. The resulting districtwide learning curves defining average annual progress through the computation curriculum provided…

Totally laparoscopic aortic surgery: comparison of the apron and retrocolic techniques in a porcine model.

PubMed

Huynh, Hai; Elkouri, Stephane; Beaudoin, Nathalie; Bruneau, Luc; Guimond, Cathie; Daniel, Véronique; Blair, Jean-François

2007-01-01

This study evaluated the learning curve for a second-year general surgery resident and compared 2 totally laparoscopic aortic surgery techniques in 10 pigs: the transretroperitoneal apron approach and the transperitoneal retrocolic approach. Five end points were compared: success rate, percentage of conversion, time required, laparoscopic anastomosis quality, and learning curve. The first 3 interventions required an open conversion. The last 7 were done without complications. Mean dissection time was significantly higher with the apron approach compared with the retrocolic approach. The total times for operation, clamping, and arteriotomy time were similar. All laparoscopic anastomoses were patent and without stenosis. The initial learning curve for laparoscopic anastomosis was relatively short for a second-year surgery resident. Both techniques resulted in satisfactory exposure of the aorta and similar mean operative and clamping time. Training on an ex vivo laparoscopic box trainer and on an animal model seems to be complementary to decrease laparoscopic anastomosis completion time.

Enhanced Night Vision Via a Combination of Poisson Interpolation and Machine Learning

DTIC Science & Technology

2006-02-01

of 0-255, they are mostly similar. The right plot shows a family of m(x, ψ) curves of ψ=2 (the most linear) through ψ=1024 (the most curved ...complicating low-light imaging. Nayar and Branzoi [04] later suggested a second variant using a DLP micromirror array to modulate the exposure, via time...255, they are mostly similar. The right plot shows a family of m(x, ψ) curves of ψ=2 (the most linear) through ψ=1024 (the most curved

Learning representations for the early detection of sepsis with deep neural networks.

PubMed

Kam, Hye Jin; Kim, Ha Young

2017-10-01

Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens. This study aimed to develop detection models for the early stage of sepsis using deep learning methodologies, and to compare the feasibility and performance of the new deep learning methodology with those of the regression method with conventional temporal feature extraction. Study group selection adhered to the InSight model. The results of the deep learning-based models and the InSight model were compared. With deep feedforward networks, the area under the ROC curve (AUC) of the models were 0.887 and 0.915 for the InSight and the new feature sets, respectively. For the model with the combined feature set, the AUC was the same as that of the basic feature set (0.915). For the long short-term memory model, only the basic feature set was applied and the AUC improved to 0.929 compared with the existing 0.887 of the InSight model. The contributions of this paper can be summarized in three ways: (i) improved performance without feature extraction using domain knowledge, (ii) verification of feature extraction capability of deep neural networks through comparison with reference features, and (iii) improved performance with feedforward neural networks using long short-term memory, a neural network architecture that can learn sequential patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generalization error analysis: deep convolutional neural network in mammography

NASA Astrophysics Data System (ADS)

Richter, Caleb D.; Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Cha, Kenny

2018-02-01

We conducted a study to gain understanding of the generalizability of deep convolutional neural networks (DCNNs) given their inherent capability to memorize data. We examined empirically a specific DCNN trained for classification of masses on mammograms. Using a data set of 2,454 lesions from 2,242 mammographic views, a DCNN was trained to classify masses into malignant and benign classes using transfer learning from ImageNet LSVRC-2010. We performed experiments with varying amounts of label corruption and types of pixel randomization to analyze the generalization error for the DCNN. Performance was evaluated using the area under the receiver operating characteristic curve (AUC) with an N-fold cross validation. Comparisons were made between the convergence times, the inference AUCs for both the training set and the test set of the original image patches without corruption, and the root-mean-squared difference (RMSD) in the layer weights of the DCNN trained with different amounts and methods of corruption. Our experiments observed trends which revealed that the DCNN overfitted by memorizing corrupted data. More importantly, this study improved our understanding of DCNN weight updates when learning new patterns or new labels. Although we used a specific classification task with the ImageNet as example, similar methods may be useful for analysis of the DCNN learning processes, especially those that employ transfer learning for medical image analysis where sample size is limited and overfitting risk is high.

Uniportal video-assisted thoracoscopic surgery: safety, efficacy and learning curve during the first 250 cases in Quebec, Canada.

PubMed

Drevet, Gabrielle; Ugalde Figueroa, Paula

2016-03-01

Video-assisted thoracoscopic surgery (VATS) using a single incision (uniportal) may result in better pain control, earlier mobilization and shorter hospital stays. Here, we review the safety and efficiency of our initial experience with uniportal VATS and evaluate our learning curve. We conducted a retrospective review of uniportal VATS using a prospectively maintained departmental database and analyzed patients who had undergone a lung anatomic resection separately from patients who underwent other resections. To assess the learning curve, we compared the first 10 months of the study period with the second 10 months. From January 2014 to August 2015, 250 patients underwent intended uniportal VATS, including 180 lung anatomic resections (72%) and 70 other resections (28%). Lung anatomic resection was successfully completed using uniportal VATS in 153 patients (85%), which comprised all the anatomic segmentectomies (29 patients), 80% (4 of 5) of the pneumonectomies and 82% (120 of 146) of the lobectomies attempted. The majority of lung anatomic resections that required conversion to thoracotomy occurred in the first half of our study period. Seventy patients underwent other uniportal VATS resections. Wedge resections were the most common of these procedures (25 patients, 35.7%). Although 24 of the 70 patients (34%) required the placement of additional ports, none required conversion to thoracotomy. Uniportal VATS was safe and feasible for both standard and complex pulmonary resections. However, when used for pulmonary anatomic resections, uniportal VATS entails a steep learning curve.

Displays mounted on cutting blocks reduce the learning curve in navigated total knee arthroplasty.

PubMed

Schnurr, Christoph; Eysel, Peer; König, Dietmar Pierre

2011-01-01

The use of computer navigation in total knee arthroplasty (TKA) improves the implant alignment but increases the operation time. Studies have shown that the operation time is further prolonged due to the surgeon's learning curve, and longer operation times have been associated with higher morbidity risks. It has been our hypothesis that an improvement in the human-machine interface might reduce the time required during the learning curve. Accordingly, we asked whether the use of navigation devices with a display fixed on the surgical instruments would reduce the operation time in navigated TKAs performed by navigation beginners. Thirty medical students were randomized and used two navigation devices in rotation: these were the Kolibri® device with an external display and the Dash® device with a display that was fixed on the cutting blocks. The time for adjustment of the tibial and femoral cutting blocks on knee models while using these devices was measured. A significant time reduction was demonstration when the Dash® device was used: The time reduction was 21% for the tibial block (p = 0.007), 40% for the femoral block (p < 0.001), and 32% for the whole procedure (p < 0.001). The integrated display, fixed on surgical instruments in a manner similar to a spirit level, seems to be more user-friendly for navigation beginners. Hence, unproductive time losses during the learning curve may be diminished.

Learning curve of hysteroscopic placement of tubal sterilization microinserts in 15 gynecologists in the Netherlands.

PubMed

Janse, Juliënne A; Pattij, Thyrza O S; Eijkemans, Marinus J C; Broekmans, Frank J; Veersema, Sebastiaan; Schreuder, Henk W R

2013-09-01

To evaluate the learning curve of hysteroscopic placement of tubal sterilization microinserts by gynecologists in the Netherlands. Prospective multicenter study (Canadian Task Force II-2). Ten community (teaching) hospitals in the Netherlands. A total of 631 women who underwent permanent sterilization by tubal microinserts. Hysteroscopic placement of tubal sterilization microinserts performed by 15 gynecologists experienced in performing operative hysteroscopy, starting from their very first placement. Effect of increasing experience in time on procedure time, pain score, successful bilateral placement, and complications. Bilateral successful placement with confirmation of adequate positioning at follow-up evaluation was achieved in 480 (76.1%) patients at first attempt and in 44 (7.0%) at second attempt. Median procedure time was 8.0 minutes (range: 3-40), and 31 (4.9%) patients were lost to follow-up evaluation. Gravidity showed to be a confounding factor and was consequently adjusted for. A learning curve was seen in a statistically significant decrease of procedure time with increasing experience. The decrease in procedure time extended to 11 to 15 cases and was followed by a plateau phase of the subsequent 60 cases. In contrast, pain scores, successful placement, and complication rate appeared not to improve with increasing experience. A learning curve for hysteroscopic tubal sterilization was seen for procedure time, but successful placement, pain score, and complication rate were not clearly influenced by increasing experience. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Learning curve and early clinical outcomes for a robotic surgery novice performing robotic single site cholecystectomy.

PubMed

Angus, Andrew A; Sahi, Saad L; McIntosh, Bruce B

2014-06-01

A rapid training protocol has been developed for robotic surgery novices to learn robotic single-incision techniques. This study assesses the learning curve and early clinical results for a robotic surgery novice starting single-site cholecystectomy. A chart review was performed on the surgeon's first 55 patients to undergo this procedure. Average patient age was 46.01 ± 4.25 (range 21-86) years and BMI was 26.57 ± 4.25 (range 19.4-36.6) kg/m(2) . The mean port placement with docking time was 11.34 ± 3.74 (range 7-23) min. Mean console time was 28.74 ± 11.04 (range 15-66) min. Average total OR time was 61.84 ± 14.66 (range 40-105) min. All procedures were successfully completed without conversion or added ports. Complications included several minor procedural gall bladder perforations and miscellaneous postoperative symptomatic complaints. Robotic single site cholecystectomy can be safely performed by a robotic novice within a minimal learning curve and have early clinical results that are comparable to the published data of robotic experts. Copyright © 2013 John Wiley & Sons, Ltd.

Novice medical students: individual patterns in the use of learning strategies and how they change during the first academic year.

PubMed

Fabry, Götz; Giesler, Marianne

2012-01-01

Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. We identified four different patterns in approaches to learning among novice medical students ("easy-going", "flexible", "problematic" and "hardworking" learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students' learning.

Novice medical students: Individual patterns in the use of learning strategies and how they change during the first academic year

PubMed Central

Fabry, Götz; Giesler, Marianne

2012-01-01

Background: Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Methods: Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. Results: We identified four different patterns in approaches to learning among novice medical students (“easy-going”, “flexible”, “problematic” and “hardworking” learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Conclusion: Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students’ learning. PMID:22916082

Validation of a structured training and assessment curriculum for technical skill acquisition in minimally invasive surgery: a randomized controlled trial.

PubMed

Palter, Vanessa N; Orzech, Neil; Reznick, Richard K; Grantcharov, Teodor P

2013-02-01

: To develop and validate an ex vivo comprehensive curriculum for a basic laparoscopic procedure. : Although simulators have been well validated as tools to teach technical skills, their integration into comprehensive curricula is lacking. Moreover, neither the effect of ex vivo training on learning curves in the operating room (OR), nor the effect on nontechnical proficiency has been investigated. : This randomized single-blinded prospective trial allocated 20 surgical trainees to a structured training and assessment curriculum (STAC) group or conventional residency training. The STAC consisted of case-based learning, proficiency-based virtual reality training, laparoscopic box training, and OR participation. After completion of the intervention, all participants performed 5 sequential laparoscopic cholecystectomies in the OR. The primary outcome measure was the difference in technical performance between the 2 groups during the first laparoscopic cholecystectomy. Secondary outcome measures included differences with respect to learning curves in the OR, technical proficiency of each sequential laparoscopic cholecystectomy, and nontechnical skills. : Residents in the STAC group outperformed residents in the conventional group in the first (P = 0.004), second (P = 0.036), third (P = 0.021), and fourth (P = 0.023) laparoscopic cholecystectomies. The conventional group demonstrated a significant learning curve in the OR (P = 0.015) in contrast to the STAC group (P = 0.032). Residents in the STAC group also had significantly higher nontechnical skills (P = 0.027). : Participating in the STAC shifted the learning curve for a basic laparoscopic procedure from the operating room into the simulation laboratory. STAC-trained residents had superior technical proficiency in the OR and nontechnical skills compared with conventionally trained residents. (The study registration ID is NCT01560494.).

Holmium laser enucleation of the prostate and retropubic prostatic adenomectomy: morbidity analysis and anesthesia considerations.

PubMed

Soto-Mesa, D; Amorín-Díaz, M; Pérez-Arviza, L; Fernández-Pello Montes, S; Martín-Huéscar, A

2015-11-01

Holmium laser enucleation of the prostate (HoLEP) is an alternative to prostatic adenomectomy for the surgical treatment of benign prostatic hypertrophy. We analyzed our learning curve for this technique, and we compared it in a secondary manner with prostatic adenomectomy. A retrospective comparative study was conducted that included the first 100 cases of HoLEP performed in our center and the latest 50 cases of retropubic adenomectomy. We collected data on the patients, the surgery, the anesthesia, the perioperative variables, the anesthesia complications and the postoperative variables, with a 6-month follow-up. We analyzed the learning curve without mentors for HoLEP and compared the characteristics of HoLEP in 2 separate phases (learning and stabilization phases) with the latest retropubic prostatic adenomectomies performed. Intradural anesthesia was the most common technique. The transfusion needs, length of stay (P<.01) and postoperative morbidity were lower for HoLEP than for adenomectomy. However, the retropubic adenomectomy group had larger initial prostate volumes (P<.001) and shorter surgical times (P<.001). Better surgical performance (P<.001) and a lower incidence of complications were observed in the HoLEP-B group (once the learning curve had been overcome) compared with the HoLEP-A group. In our center, HoLEP was introduced as a valid alternative to open retropubic adenomectomy, with excellent results in terms of morbidity and reduced hospital stay. In terms of the learning curve, we consider that approximately 50 patients (without mentor) is an appropriate cutoff. Local anesthesia is a good choice for the anesthesia technique. Copyright © 2014 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Sex is not everything: the role of gender in early performance of a fundamental laparoscopic skill.

PubMed

Kolozsvari, Nicoleta O; Andalib, Amin; Kaneva, Pepa; Cao, Jiguo; Vassiliou, Melina C; Fried, Gerald M; Feldman, Liane S

2011-04-01

Existing literature on the acquisition of surgical skills suggests that women generally perform worse than men. This literature is limited by looking at an arbitrary number of trials and not adjusting for potential confounders. The objective of this study was to evaluate the impact of gender on the learning curve for a fundamental laparoscopic task. Thirty-two medical students performed the FLS peg transfer task and their scores were plotted to generate a learning curve. Nonlinear regression was used to estimate learning plateau and learning rate. Variables that may affect performance were assessed using a questionnaire. Innate visual-spatial abilities were evaluated using tests for spatial orientation, spatial scanning, and perceptual abilities. Score on first peg transfer attempt, learning plateau, and learning rate were compared for men and women using Student's t test. Innate abilities were correlated to simulator performance using Pearson's coefficient. Multivariate linear regression was used to investigate the effect of gender on early laparoscopic performance after adjusting for factors found significant on univariate analysis. Statistical significance was defined as P < 0.05. Nineteen men and 13 women participated in the study; 30 were right-handed, 12 reported high interest in surgery, and 26 had video game experience. There were no differences between men and women in initial peg transfer score, learning plateau, or learning rate. Initial peg transfer score and learning rate were higher in subjects who reported having a high interest in surgery (P = 0.02, P = 0.03). Initial score also correlated with perceptual ability score (P = 0.03). In multivariate analysis, only surgical interest remained a significant predictor of score on first peg transfer (P = 0.03) and learning rate (P = 0.02), while gender had no significant relationship to early performance. Gender did not affect the learning curve for a fundamental laparoscopic task, while interest in surgery and perceptual abilities did influence early performance.

The learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease.

PubMed

Novotný, Tomáš; Dvorák, Martin; Staffa, Robert

2011-02-01

Since the end of the 20th century, robot-assisted surgery has been finding its role among other minimally invasive methods. Vascular surgery seems to be another specialty in which the benefits of this technology can be expected. Our objective was to assess the learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease in a group of 40 patients. Between May 2006 and January 2010, 40 patients (32 men, 8 women), who were a median age of 58 years (range, 48-75 years), underwent 40 robot-assisted laparoscopic aortofemoral reconstructions. Learning curve estimations were used for anastomosis, clamping, and operative time assessment. For conversion rate evaluation, the cumulative summation (CUSUM) technique was used. Statistical analysis comparing the first and second half of our group, and unilateral-to-bilateral reconstructions were performed. We created 21 aortofemoral and 19 aortobifemoral bypasses. The median proximal anastomosis time was 23 minutes (range, 18-50 minutes), median clamping time was 60 minutes (range, 40-95 minutes), and median operative time was 295 minutes (range, 180-475 minutes). The 30-day mortality rate was 0%, and no graft or wound infection or cardiopulmonary or hepatorenal complications were observed. During the median 18-month follow-up (range, 2-48 months), three early graft occlusions occurred (7%). After reoperations, the secondary patency of reconstructions was 100%. Data showed a typical short learning curve for robotic proximal anastomosis creation with anastomosis and clamping time reduction. The operative time learning curve was flat, confirming the procedure's complexity. There were two conversions to open surgery. CUSUM analysis confirmed that an acceptable conversion rate set at 5% was achieved. Comparing the first and second half of our group, all recorded times showed statistically significant improvements. Differences between unilateral and bilateral reconstructions were not statistically significant. Our results show that the success rate of robot-assisted laparoscopic aortofemoral bypass grafting is high and the complication rate is low. Anastomosis creation, one of the main difficulties of laparoscopic bypass grafting, has been overcome using the robotic operating system and its learning curve is short. However, the endoscopic dissection of the aortoiliac segment remains the most difficult part of the operation and should be addressed in further development of the method to reduce the operative times. Long-term results and potential benefits of this minimally invasive method have to be verified by randomized controlled clinical trials. Copyright © 2011 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Photometric Supernova Classification with Machine Learning

NASA Astrophysics Data System (ADS)

Lochner, Michelle; McEwen, Jason D.; Peiris, Hiranya V.; Lahav, Ofer; Winter, Max K.

2016-08-01

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models to curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k-nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.

Endoscopic sleeve gastroplasty: the learning curve.

PubMed

Hill, Christine; El Zein, Mohamad; Agnihotri, Abhishek; Dunlap, Margo; Chang, Angela; Agrawal, Alison; Barola, Sindhu; Ngamruengphong, Saowanee; Chen, Yen-I; Kalloo, Anthony N; Khashab, Mouen A; Kumbhari, Vivek

2017-09-01

 Endoscopic sleeve gastroplasty (ESG) is gaining traction as a minimally invasive bariatric treatment. Concern that the learning curve may be slow, even among those proficient in endoscopic suturing, is a barrier to widespread implementation of the procedure. Therefore, we aimed to define the learning curve for ESG in a single endoscopist experienced in endoscopic suturing who participated in a 1-day ESG training program.  Consecutive patients who underwent ESG between February 2016 and November 2016 were included. The performing endoscopist, who is proficient in endoscopic suturing for non-ESG procedures, participated in a 1-day ESG training session before offering ESG to patients. The outcome measurements were length of procedure (LOP) and number of plications per procedure. Nonlinear regression was used to determine the learning plateau and calculate the learning rate.  Twenty-one consecutive patients (8 males), with mean age 47.7 ± 11.2 years and mean body mass index 41.8 ± 8.5 kg/m 2 underwent ESG. LOP decreased significantly across consecutive procedures, with a learning plateau at 101.5 minutes and a learning rate of 7 cases ( P  = 0.04). The number of plications per procedure also decreased significantly across consecutive procedures, with a plateau at 8 sutures and a learning rate of 9 cases ( P  < 0.001). Further, the average time per plication decreased significantly with consecutive procedures, reaching a plateau at 9 procedures ( P  < 0.001).  Endoscopists experienced in endoscopic suturing are expected to achieve a reduction in LOP and number of plications per procedure in successive cases, with progress plateauing at 7 and 9 cases, respectively.

Acquisition of neural learning in cerebellum and cerebral cortex for smooth pursuit eye movements

PubMed Central

Li, Jennifer X.; Medina, Javier F.; Frank, Loren M.; Lisberger, Stephen G.

2011-01-01

We have evaluated the emergence of neural learning in the frontal eye fields (FEFSEM) and the floccular complex of the cerebellum while monkeys learned a precisely-timed change in the direction of pursuit eye movement. For each neuron, we measured the time course of changes in neural response across a learning session that comprised at least 100 repetitions of an instructive change in target direction. In both areas, the average population learning curves tracked the behavioral changes with high fidelity, consistent with possible roles in driving learning. However, the learning curves of individual neurons sometimes bore little relation to the smooth, monotonic progression of behavioral learning. In the FEFSEM, neural learning was episodic. For individual neurons, learning appeared at different times during the learning session and sometimes disappeared by the end of the session. Different FEFSEM neurons expressed maximal learning at different times relative to the acquisition of behavioral learning. In the floccular complex, many Purkinje cells acquired learned simple-spike responses according to the same time course as behavioral learning and retained their learned responses throughout the learning session. A minority of Purkinje cells acquired learned responses late in the learning session, after behavioral learning had reached an asymptote. We conclude that learning in single neurons can follow a very different time course from behavioral learning. Both the FEFSEM and the floccular complex contain representations of multiple temporal components of learning, with different neurons contributing to learning at different times during the acquisition of a learned movement. PMID:21900551

Involvement of Working Memory in College Students' Sequential Pattern Learning and Performance

ERIC Educational Resources Information Center

Kundey, Shannon M. A.; De Los Reyes, Andres; Rowan, James D.; Lee, Bern; Delise, Justin; Molina, Sabrina; Cogdill, Lindsay

2013-01-01

When learning highly organized sequential patterns of information, humans and nonhuman animals learn rules regarding the hierarchical structures of these sequences. In three experiments, we explored the role of working memory in college students' sequential pattern learning and performance in a computerized task involving a sequential…

Optimizing a Workplace Learning Pattern: A Case Study from Aviation

ERIC Educational Resources Information Center

Mavin, Timothy John; Roth, Wolff-Michael

2015-01-01

Purpose: This study aims to contribute to current research on team learning patterns. It specifically addresses some negative perceptions of the job performance learning pattern. Design/methodology/approach: Over a period of three years, qualitative and quantitative data were gathered on pilot learning in the workplace. The instructional modes…

Analysis of preexistent vertebral rotation in the normal infantile, juvenile, and adolescent spine.

PubMed

Janssen, Michiel M A; Kouwenhoven, Jan-Willem M; Schlösser, Tom P C; Viergever, Max A; Bartels, Lambertus W; Castelein, René M; Vincken, Koen L

2011-04-01

Vertebral rotation was systematically analyzed in the normal, nonscoliotic thoracic spine of children aged 0 to 16 years. Subgroups were created to match the infantile, juvenile, and adolescent age groups according to the criteria of the Scoliosis Research Society. To determine whether a distinct pattern of vertebral rotation in the transverse plane exists in the normal, nonscoliotic infantile, juvenile, and adolescent spine. We assume that, once the spine starts to deteriorate into a scoliotic deformity, it will follow a preexisting rotational pattern. Recently, we identified a rotational pattern in the normal nonscoliotic adult spine that corresponds to the most common curve types in adolescent idiopathic scoliosis. In infantile idiopathic scoliosis, curves are typically left sided and boys are affected more often than girls, whereas in adolescent idiopathic scoliosis, the thoracic curve is typically right sided and predominantly girls are affected. The present study is the first systematic analysis of vertebral rotation in the normal children's spine. Vertebral rotation in the transverse plane of T2-T12 was measured by using a semiautomatic method on 146 computed tomographic scans of children (0-16 years old) without clinical or radiologic evidence of spinal pathology. Scans were mainly made for reasons such as recurrent respiratory tract infections, malignancies, or immune disorders. Vertebral rotational patterns were analyzed in the infantile (0-3-year-old), juvenile (4-9-year-old), and adolescent (10-16-year-old) boys and girls. In the infantile spine, vertebrae T2-T6 were significantly rotated to the left (P < 0.001). In the juvenile spine, T4 was significantly rotated to the left. In the adolescent spine, T6-T12 were significantly rotated to the right (P ≤ 0.001). Rotation to the left was more pronounced in infantile boys than in the girls (P = 0.023). In juvenile and adolescent children, no statistical differences in rotation were found between the sexes. These data support the hypothesis that the direction of the spinal curve in idiopathic scoliosis is determined by the built-in rotational pattern that the spine exhibits at the time of onset. The well-known predominance of right-sided thoracic curves in adolescent idiopathic scoliosis and left-sided curves in infantile idiopathic scoliosis can be explained by the observed patterns of vertebral rotation that preexist at the corresponding age.

Learning curves of theta/beta neurofeedback in children with ADHD.

PubMed

Janssen, Tieme W P; Bink, Marleen; Weeda, Wouter D; Geladé, Katleen; van Mourik, Rosa; Maras, Athanasios; Oosterlaan, Jaap

2017-05-01

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and specificity of this intervention. A total of 38 children (aged between 7 and 13 years) with a DSM-IV-TR diagnosis of ADHD, completed on average 29 sessions of theta (4-8 Hz)/beta (13-20 Hz) neurofeedback training. Dependent variables included training-related measures as well as theta and beta power during baseline and training runs for each session. Learning effects were analyzed both within and between sessions. To further specify findings, individual learning curves were explored and correlated with behavioral changes in ADHD symptoms. Over the course of the training, there was a linear increase in participants' mean training level, highest obtained training level and the number of earned credits (range b = 0.059, -0.750, p < 0.001). Theta remained unchanged over the course of the training, while beta activity increased linearly within training sessions (b = 0.004, 95% CI = [0.0013-0.0067], p = 0.005) and over the course of the intervention (b = 0.0052, 95% CI = [0.0039-0.0065], p < 0.001). In contrast to the group analyses, significant individual learning curves were found for both theta and beta over the course of the intervention in 39 and 53%, respectively. Individual learning curves were not significantly correlated with behavioral changes. This study shows that children with ADHD can gain control over EEG states during neurofeedback, although a lack of behavioral correlates may indicate insufficient transfer to daily functioning, or to confounding reinforcement of electromyographic activity. This trial is registered at the US National Institutes of Health (ClinicalTrials.gov, ref. no: NCT01363544); https://clinicaltrials.gov/show/NCT01363544 .

Implicit learning in cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia).

PubMed

Locurto, Charles; Fox, Maura; Mazzella, Andrea

2015-06-01

There is considerable interest in the conditions under which human subjects learn patterned information without explicit instructions to learn that information. This form of learning, termed implicit or incidental learning, can be approximated in nonhumans by exposing subjects to patterned information but delivering reinforcement randomly, thereby not requiring the subjects to learn the information in order to be reinforced. Following acquisition, nonhuman subjects are queried as to what they have learned about the patterned information. In the present experiment, we extended the study of implicit learning in nonhumans by comparing two species, cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia), on an implicit learning task that used an artificial grammar to generate the patterned elements for training. We equated the conditions of training and testing as much as possible between the two species. The results indicated that both species demonstrated approximately the same magnitude of implicit learning, judged both by a random test and by choice tests between pairs of training elements. This finding suggests that the ability to extract patterned information from situations in which such learning is not demanded is of longstanding origin.

Instructional Patterns: Strategies for Maximizing Student Learning [with CD-ROM

ERIC Educational Resources Information Center

Holt, Larry Charles; Kysilka, Marcella L.

2005-01-01

"Instructional Patterns: Strategies for Maximizing Student Learning" examines instruction from the learners' point of view by showing how instructional patterns can be used to maximize the potential for students to learn. This book explores the interactive patterns that exist in today's classroom and demonstrates how teachers can…

A vertical-energy-thresholding procedure for data reduction with multiple complex curves.

PubMed

Jung, Uk; Jeong, Myong K; Lu, Jye-Chyi

2006-10-01

Due to the development of sensing and computer technology, measurements of many process variables are available in current manufacturing processes. It is very challenging, however, to process a large amount of information in a limited time in order to make decisions about the health of the processes and products. This paper develops a "preprocessing" procedure for multiple sets of complicated functional data in order to reduce the data size for supporting timely decision analyses. The data type studied has been used for fault detection, root-cause analysis, and quality improvement in such engineering applications as automobile and semiconductor manufacturing and nanomachining processes. The proposed vertical-energy-thresholding (VET) procedure balances the reconstruction error against data-reduction efficiency so that it is effective in capturing key patterns in the multiple data signals. The selected wavelet coefficients are treated as the "reduced-size" data in subsequent analyses for decision making. This enhances the ability of the existing statistical and machine-learning procedures to handle high-dimensional functional data. A few real-life examples demonstrate the effectiveness of our proposed procedure compared to several ad hoc techniques extended from single-curve-based data modeling and denoising procedures.

Current Status of Robot-Assisted Radical Cystectomy: What is the Real Benefit?

PubMed

Takenaka, Atsushi

2015-09-01

In recent years, robot-assisted radical cystectomy has received attention worldwide as a useful procedure that helps to overcome the limitations of open radical cystectomy. We compared the surgical technique, perioperative and oncological outcomes, and learning curve of robot-assisted radical cystectomy with those of open radical cystectomy. The indications for robot-assisted radical cystectomy are identical to those of open radical cystectomy. Relative contraindications are due to patient positioning in the Trendelenburg position for long periods. Urinary diversion is performed either extracorporeally with a small skin incision or intracorporeally with a totally robotic-assisted maneuver. Accordingly, robot-assisted radical cystectomy can be performed safely with an acceptable operative time, little blood loss, and low transfusion rates. The lymph node yield and positive surgical margin rate were not significantly different between robot-assisted radical cystectomy and open radical cystectomy. The survival rates after robot-assisted radical cystectomy are estimated to be similar to that after open radical cystectomy. However, the recurrence pattern is different between robot-assisted radical cystectomy and open radical cystectomy, i.e., extrapelvic lymph node recurrence and peritoneal carcinomatosis were more frequently found in patients who underwent robot-assisted radical cystectomy than in those who underwent open radical cystectomy. Further validation is necessary to prove the feasibility of oncological control. A steep learning curve is one of the benefits of the new technique. The experience of only 50 robot-assisted radical prostatectomies is a minimum requirement for performing feasible robot-assisted radical cystectomy, and surgeons who have performed only 30 surgeries can reach an acceptable level of quality for robot-assisted radical cystectomy.

Assessing Teachers' Competencies to Read and Interpret Graphs from Learning Progress Assessment: Results from Tests and Interviews

ERIC Educational Resources Information Center

Zeuch, Nina; Förster, Natalie; Souvignier, Elmar

2017-01-01

Learning progress assessment (LPA) provides formative information about effectiveness of instructional decisions. Learning curves are usually presented as graphical illustrations. However, little is known about teachers understanding and interpreting of graphically presented information. An instrument to measure competencies in reading graphs from…

On-line Machine Learning and Event Detection in Petascale Data Streams

NASA Astrophysics Data System (ADS)

Thompson, David R.; Wagstaff, K. L.

2012-01-01

Traditional statistical data mining involves off-line analysis in which all data are available and equally accessible. However, petascale datasets have challenged this premise since it is often impossible to store, let alone analyze, the relevant observations. This has led the machine learning community to investigate adaptive processing chains where data mining is a continuous process. Here pattern recognition permits triage and followup decisions at multiple stages of a processing pipeline. Such techniques can also benefit new astronomical instruments such as the Large Synoptic Survey Telescope (LSST) and Square Kilometre Array (SKA) that will generate petascale data volumes. We summarize some machine learning perspectives on real time data mining, with representative cases of astronomical applications and event detection in high volume datastreams. The first is a "supervised classification" approach currently used for transient event detection at the Very Long Baseline Array (VLBA). It injects known signals of interest - faint single-pulse anomalies - and tunes system parameters to recover these events. This permits meaningful event detection for diverse instrument configurations and observing conditions whose noise cannot be well-characterized in advance. Second, "semi-supervised novelty detection" finds novel events based on statistical deviations from previous patterns. It detects outlier signals of interest while considering known examples of false alarm interference. Applied to data from the Parkes pulsar survey, the approach identifies anomalous "peryton" phenomena that do not match previous event models. Finally, we consider online light curve classification that can trigger adaptive followup measurements of candidate events. Classifier performance analyses suggest optimal survey strategies, and permit principled followup decisions from incomplete data. These examples trace a broad range of algorithm possibilities available for online astronomical data mining. This talk describes research performed at the Jet Propulsion Laboratory, California Institute of Technology. Copyright 2012, All Rights Reserved. U.S. Government support acknowledged.

Guiding curve based on the normal breathing as monitored by thermocouple for regular breathing.

PubMed

Lim, Sangwook; Park, Sung Ho; Ahn, Seung Do; Suh, Yelin; Shin, Seong Soo; Lee, Sang-wook; Kim, Jong Hoon; Choi, Eun Kyoung; Yi, Byong Yong; Kwon, Soo Il; Kim, Sookil; Jeung, Tae Sig

2007-11-01

Adapting radiation fields to a moving target requires information continuously on the location of internal target by detecting it directly or indirectly. The aim of this study is to make the breathing regular effectively with minimizing stress to the patient. A system for regulating patient's breath consists of a respiratory monitoring mask (ReMM), a thermocouple module, a screen, inner earphones, and a personal computer. A ReMM with thermocouple was developed previously to measure the patient's respiration. A software was written in LabView 7.0 (National Instruments, TX), which acquires respiration signal and displays its pattern. Two curves are displayed on the screen: One is a curve indicating the patient's current breathing pattern; the other is a guiding curve, which is iterated with one period of the patient's normal breathing curve. The guiding curves were acquired for each volunteer before they breathed with guidance. Ten volunteers participated in this study to evaluate this system. A cycle of the representative guiding curve was acquired by monitoring each volunteer's free breathing with ReMM and was then generated iteratively. The regularity was compared between a free breath curve and a guided breath curve by measuring standard deviations of amplitudes and periods of two groups of breathing. When the breathing was guided, the standard deviation of amplitudes and periods on average were reduced from 0.0029 to 0.00139 (arbitrary units) and from 0.359 s to 0.202 s, respectively. And the correlation coefficients between breathing curves and guiding curves were greater than 0.99 for all volunteers. The regularity was improved statistically when the guiding curve was used.

Stochastic Gain in Population Dynamics

NASA Astrophysics Data System (ADS)

Traulsen, Arne; Röhl, Torsten; Schuster, Heinz Georg

2004-07-01

We introduce an extension of the usual replicator dynamics to adaptive learning rates. We show that a population with a dynamic learning rate can gain an increased average payoff in transient phases and can also exploit external noise, leading the system away from the Nash equilibrium, in a resonancelike fashion. The payoff versus noise curve resembles the signal to noise ratio curve in stochastic resonance. Seen in this broad context, we introduce another mechanism that exploits fluctuations in order to improve properties of the system. Such a mechanism could be of particular interest in economic systems.

Analysis of the vitreoretinal surgery learning curve.

PubMed

Martín-Avià, J; Romero-Aroca, P

2017-06-01

To describe intra- and post-operative complications, as well as the evolution of the surgical technique in first 4years of work of a novice retina surgeon, and evaluate minimal learning time required to reduce its complications, deciding which pathologies should still be referred to higher level hospitals, until further experience may be achieved. A study was conducted on patients that had undergone vitreoretinal surgery by a novice surgeon in Tarragona between 23rd October 2007 and 31st December 2011. The primary diagnosis, surgeon learning time, surgical technique, intra-operative and post-operative complications were recorded. A total of 247 surgeries were studied. The percentage of use of 20G and 23G calibres during the time, marks a change towards trans-conjunctival surgery from the ninth trimester (98 surgeries). Surgical complications decreased towards twelfth trimester (130 surgeries) with an increase in the previous months. The shift towards 23G technique around 100 surgeries is interpreted as greater comfort and safety by the surgeon. Increased surgical complications during the following months until its decline around 130 surgeries can be interpreted as an 'overconfidence'. It is arguable that the learning curve is slower than what the surgeon believes. An individual analysis of the complications and surgical outcomes is recommended to ascertain the status of the learning curve. Copyright © 2016 Sociedad Española de Oftalmología. Publicado por Elsevier España, S.L.U. All rights reserved.

Development of a Portable Motor Learning Laboratory (PoMLab)

PubMed Central

Shinya, Masahiro

2016-01-01

Most motor learning experiments have been conducted in a laboratory setting. In this type of setting, a huge and expensive manipulandum is frequently used, requiring a large budget and wide open space. Subjects also need to travel to the laboratory, which is a burden for them. This burden is particularly severe for patients with neurological disorders. Here, we describe the development of a novel application based on Unity3D and smart devices, e.g., smartphones or tablet devices, that can be used to conduct motor learning experiments at any time and in any place, without requiring a large budget and wide open space and without the burden of travel on subjects. We refer to our application as POrtable Motor learning LABoratory, or PoMLab. PoMLab is a multiplatform application that is available and sharable for free. We investigated whether PoMLab could be an alternative to the laboratory setting using a visuomotor rotation paradigm that causes sensory prediction error, enabling the investigation of how subjects minimize the error. In the first experiment, subjects could adapt to a constant visuomotor rotation that was abruptly applied at a specific trial. The learning curve for the first experiment could be modeled well using a state space model, a mathematical model that describes the motor leaning process. In the second experiment, subjects could adapt to a visuomotor rotation that gradually increased each trial. The subjects adapted to the gradually increasing visuomotor rotation without being aware of the visuomotor rotation. These experimental results have been reported for conventional experiments conducted in a laboratory setting, and our PoMLab application could reproduce these results. PoMLab can thus be considered an alternative to the laboratory setting. We also conducted follow-up experiments in university physical education classes. A state space model that was fit to the data obtained in the laboratory experiments could predict the learning curves obtained in the follow-up experiments. Further, we investigated the influence of vibration function, weight, and screen size on learning curves. Finally, we compared the learning curves obtained in the PoMLab experiments to those obtained in the conventional reaching experiments. The results of the in-class experiments show that PoMLab can be used to conduct motor learning experiments at any time and place. PMID:27348223

Development of a Portable Motor Learning Laboratory (PoMLab).

PubMed

Takiyama, Ken; Shinya, Masahiro

2016-01-01

Most motor learning experiments have been conducted in a laboratory setting. In this type of setting, a huge and expensive manipulandum is frequently used, requiring a large budget and wide open space. Subjects also need to travel to the laboratory, which is a burden for them. This burden is particularly severe for patients with neurological disorders. Here, we describe the development of a novel application based on Unity3D and smart devices, e.g., smartphones or tablet devices, that can be used to conduct motor learning experiments at any time and in any place, without requiring a large budget and wide open space and without the burden of travel on subjects. We refer to our application as POrtable Motor learning LABoratory, or PoMLab. PoMLab is a multiplatform application that is available and sharable for free. We investigated whether PoMLab could be an alternative to the laboratory setting using a visuomotor rotation paradigm that causes sensory prediction error, enabling the investigation of how subjects minimize the error. In the first experiment, subjects could adapt to a constant visuomotor rotation that was abruptly applied at a specific trial. The learning curve for the first experiment could be modeled well using a state space model, a mathematical model that describes the motor leaning process. In the second experiment, subjects could adapt to a visuomotor rotation that gradually increased each trial. The subjects adapted to the gradually increasing visuomotor rotation without being aware of the visuomotor rotation. These experimental results have been reported for conventional experiments conducted in a laboratory setting, and our PoMLab application could reproduce these results. PoMLab can thus be considered an alternative to the laboratory setting. We also conducted follow-up experiments in university physical education classes. A state space model that was fit to the data obtained in the laboratory experiments could predict the learning curves obtained in the follow-up experiments. Further, we investigated the influence of vibration function, weight, and screen size on learning curves. Finally, we compared the learning curves obtained in the PoMLab experiments to those obtained in the conventional reaching experiments. The results of the in-class experiments show that PoMLab can be used to conduct motor learning experiments at any time and place.

Rotation Periods and Photometric Amplitudes for Cool Stars with TESS

NASA Astrophysics Data System (ADS)

Andrews, Hannah; Dominguez, Zechariah; Johnson, Sara; Buzasi, Derek L.

2018-06-01

The original Kepler mission observed 200000 stars in the same field nearly continuously for over four years, generating an unparalleled set of stellar rotation curves and new insights into the correlation between rotation periods and photometric variability on the lower main sequence. The continuation of Kepler in the guise of K2 has allowed us to examine a stellar sample comparable in size to that observed with Kepler, but drawn from new stellar populations. However, K2 observed each field for at most three months, limiting the inferences that can be drawn, particularly for older, slower-rotating stars. The upcoming TESS spacecraft will provide light curves for perhaps two orders of magnitude more stars, but with time windows as short as 27 days. In this work, we resample Kepler light curves using the TESS observing window, and study what can be learned from high-precision light curves of such short lengths, and how to compare those results to what we have learned from Kepler.

6. DETAIL OF GUSSET WITH CURVE ANGLE IRON AND TWISTED ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. DETAIL OF GUSSET WITH CURVE ANGLE IRON AND TWISTED STRIPS, FORMING SUN RAY PATTERN. LATTICE RAILING AT LOWER RIGHT. - River Road Bridge, Spanning Spring Creek in Spring Creek Township, Hallton, Elk County, PA

14. DETAIL OF GUSSET WITH CURVE ANGLE IRON AND TWISTED ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. DETAIL OF GUSSET WITH CURVE ANGLE IRON AND TWISTED STRIPS, FORMING SUN RAY PATTERN. LATTICE RAILING AT LOWER RIGHT. - River Road Bridge, Spanning Spring Creek in Spring Creek Township, Hallton, Elk County, PA

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

NASA Astrophysics Data System (ADS)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

Using machine learning and surface reconstruction to accurately differentiate different trajectories of mood and energy dysregulation in youth.

PubMed

Versace, Amelia; Sharma, Vinod; Bertocci, Michele A; Bebko, Genna; Iyengar, Satish; Dwojak, Amanda; Bonar, Lisa; Perlman, Susan B; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Diwadkar, Vaibhav A; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Frazier, Thomas W; Arnold, L Eugene; Fristad, Mary A; Youngstrom, Eric A; Horwitz, Sarah M; Findling, Robert L; Phillips, Mary L

2017-01-01

Difficulty regulating positive mood and energy is a feature that cuts across different pediatric psychiatric disorders. Yet, little is known regarding the neural mechanisms underlying different developmental trajectories of positive mood and energy regulation in youth. Recent studies indicate that machine learning techniques can help elucidate the role of neuroimaging measures in classifying individual subjects by specific symptom trajectory. Cortical thickness measures were extracted in sixty-eight anatomical regions covering the entire brain in 115 participants from the Longitudinal Assessment of Manic Symptoms (LAMS) study and 31 healthy comparison youth (12.5 y/o;-Male/Female = 15/16;-IQ = 104;-Right/Left handedness = 24/5). Using a combination of trajectories analyses, surface reconstruction, and machine learning techniques, the present study aims to identify the extent to which measures of cortical thickness can accurately distinguish youth with higher (n = 18) from those with lower (n = 34) trajectories of manic-like behaviors in a large sample of LAMS youth (n = 115; 13.6 y/o; M/F = 68/47, IQ = 100.1, R/L = 108/7). Machine learning analyses revealed that widespread cortical thickening in portions of the left dorsolateral prefrontal cortex, right inferior and middle temporal gyrus, bilateral precuneus, and bilateral paracentral gyri and cortical thinning in portions of the right dorsolateral prefrontal cortex, left ventrolateral prefrontal cortex, and right parahippocampal gyrus accurately differentiate (Area Under Curve = 0.89;p = 0.03) youth with different (higher vs lower) trajectories of positive mood and energy dysregulation over a period up to 5years, as measured by the Parent General Behavior Inventory-10 Item Mania Scale. Our findings suggest that specific patterns of cortical thickness may reflect transdiagnostic neural mechanisms associated with different temporal trajectories of positive mood and energy dysregulation in youth. This approach has potential to identify patterns of neural markers of future clinical course.

A Growth Curve Analysis of Novel Word Learning by Sequential Bilingual Preschool Children

ERIC Educational Resources Information Center

Kan, Pui Fong; Kohnert, Kathryn

2012-01-01

Longitudinal word learning studies which control for experience can advance understanding of language learning and potential intra- and inter-language relationships in developing bilinguals. We examined novel word learning in both the first (L1) and the second (L2) languages of bilingual children. The rate and shape of change as well as the role…

Life Span as the Measure of Performance and Learning in a Business Gaming Simulation

ERIC Educational Resources Information Center

Thavikulwat, Precha

2012-01-01

This study applies the learning curve method of measuring learning to participants of a computer-assisted business gaming simulation that includes a multiple-life-cycle feature. The study involved 249 participants. It verified the workability of the feature and estimated the participants' rate of learning at 17.4% for every doubling of experience.…

Tools to Make Online Students and Community Partners in a Service Learning Project More "AT-EASE"--Evidence from a Finance Class

ERIC Educational Resources Information Center

Butchey, Deanne

2014-01-01

The impact of service learning as a pedagogy to ensure efficient and effective experiential learning is well recognized, but in business schools, there is a perception that a steep learning curve exists for the students, faculty, and community. We use a tool to motivate and build competence in participants of a service learning project undertaken…

Issues in Researching Self-Regulated Learning as Patterns of Events

ERIC Educational Resources Information Center

Winne, Philip H.

2014-01-01

New methods for gathering and analyzing data about events that comprise self-regulated learning (SRL) support discoveries about patterns among events and tests of hypotheses about roles patterns play in learning. Five such methodologies are discussed in the context of four key questions that shape investigations into patterns in SRL. A framework…

Electron-beam lithography with character projection exposure for throughput enhancement with line-edge quality optimization

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Maruyama, Satoshi; Mita, Yoshio; Ikeda, Makoto; Asada, Kunihiro

2016-03-01

Among various electron-beam lithography (EBL) techniques, variable-shaped beam (VSB) and character projection (CP) methods have attracted many EBL users for their high-throughput feature, but they are considered to be more suited to small-featured VLSI fabrication with regularly-arranged layouts like standard-cell logics and memory arrays. On the other hand, non-VLSI applications like photonics, MEMS, MOEMS, and so on, have not been fully utilized the benefit of CP method due to their wide variety of layout patterns. In addition, the stepwise edge shapes by VSB method often causes intolerable edge roughness to degrade device characteristics from its intended performance with smooth edges. We proposed an overall EBL methodology applicable to wade-variety of EBL applications utilizing VSB and CP methods. Its key idea is in our layout data conversion algorithm that decomposes curved or oblique edges of arbitrary layout patterns into CP shots. We expect significant reduction in EB shot count with a CP-bordered exposure data compared to the corresponding VSB-alone conversion result. Several CP conversion parameters are used to optimize EB exposure throughput, edge quality, and resultant device characteristics. We demonstrated out methodology using the leading-edge VSB/CP EBL tool, ADVANTEST F7000S-VD02, with high resolution Hydrogen Silsesquioxane (HSQ) resist. Through our experiments of curved and oblique edge lithography under various data conversion conditions, we learned correspondence of the conversion parameters to the resultant edge roughness and other conditions. They will be utilized as the fundamental data for further enhancement of our EBL strategy for optimized EB exposure.

A Comparative Rugoscopic Study of the Dentate and Edentulous Individuals in the South Indian Population

PubMed Central

Rajguru, Jagdish Prasad; Somayaji, Nagaveni S.; Masthan, K. M. K.; Babu, Aravindha N.; Mohanty, Neeta

2014-01-01

This study analyzes the rugae pattern in dentulous and edentulous patients and also evaluates the association of rugae pattern between males and females. Aims and Objectives. This study aims to investigate rugae patterns in dentulous and edentulous patients of both sexes in South Indian population and to find whether palatoscopy is a useful tool in human identification. Materials and Methods. Four hundred outpatients from Sree Balaji Dental College and Hospital, Chennai, were included in the study. The study group was equally divided between the sexes, which was further categorized into 100 dentulous and edentulous patients, respectively. Results. The edentulous male showed the highest mean of wavy pattern and total absence of circular pattern while the edentulous female group showed the highest mean of curved pattern and total absence of nonspecific pattern, while dentate population showed similar value as that of the overall population such as straight, wavy, and curved patterns. Conclusion. The present study concludes that there is similar rugae pattern of distribution between male and female dentate population while there is varied pattern between the sexes of edentulous population. However, the most predominant patterns were straight, wavy, and circular patterns. PMID:24605051

The learning curve for narrow-band imaging in the diagnosis of precancerous gastric lesions by using Web-based video.

PubMed

Dias-Silva, Diogo; Pimentel-Nunes, Pedro; Magalhães, Joana; Magalhães, Ricardo; Veloso, Nuno; Ferreira, Carlos; Figueiredo, Pedro; Moutinho, Pedro; Dinis-Ribeiro, Mário

2014-06-01

A simplified narrow-band imaging (NBI) endoscopy classification of gastric precancerous and cancerous lesions was derived and validated in a multicenter study. This classification comes with the need for dissemination through adequate training. To address the learning curve of this classification by endoscopists with differing expertise and to assess the feasibility of a YouTube-based learning program to disseminate it. Prospective study. Five centers. Six gastroenterologists (3 trainees, 3 fully trained endoscopists [FTs]). Twenty tests provided through a Web-based program containing 10 randomly ordered NBI videos of gastric mucosa were taken. Feedback was sent 7 days after every test submission. Measures of accuracy of the NBI classification throughout the time. From the first to the last 50 videos, a learning curve was observed with a 10% increase in global accuracy, for both trainees (from 64% to 74%) and FTs (from 56% to 65%). After 200 videos, sensitivity and specificity of 80% and higher for intestinal metaplasia were observed in half the participants, and a specificity for dysplasia greater than 95%, along with a relevant likelihood ratio for a positive result of 7 to 28 and likelihood ratio for a negative result of 0.21 to 0.82, were achieved by all of the participants. No constant learning curve was observed for the identification of Helicobacter pylori gastritis and sensitivity to dysplasia. The trainees had better results in all of the parameters, except specificity for dysplasia, compared with the FTs. Globally, participants agreed that the program's structure was adequate, except on the feedback, which should have consisted of a more detailed explanation of each answer. No formal sample size estimate. A Web-based learning program could be used to teach and disseminate classifications in the endoscopy field. In this study, an NBI classification for gastric mucosal features seems to be easily learned for the identification of gastric preneoplastic lesions. Copyright © 2014 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Moderate Levels of Activation Lead to Forgetting In the Think/No-Think Paradigm

PubMed Central

Detre, Greg J.; Natarajan, Annamalai; Gershman, Samuel J.; Norman, Kenneth A.

2013-01-01

Using the think/no-think paradigm (Anderson & Green, 2001), researchers have found that suppressing retrieval of a memory (in the presence of a strong retrieval cue) can make it harder to retrieve that memory on a subsequent test. This effect has been replicated numerous times, but the size of the effect is highly variable. Also, it is unclear from a neural mechanistic standpoint why preventing recall of a memory now should impair your ability to recall that memory later. Here, we address both of these puzzles using the idea, derived from computational modeling and studies of synaptic plasticity, that the function relating memory activation to learning is U-shaped, such that moderate levels of memory activation lead to weakening of the memory and higher levels of activation lead to strengthening. According to this view, forgetting effects in the think/no-think paradigm occur when the suppressed item activates moderately during the suppression attempt, leading to weakening; the effect is variable because sometimes the suppressed item activates strongly (leading to strengthening) and sometimes it does not activate at all (in which case no learning takes place). To test this hypothesis, we ran a think/no-think experiment where participants learned word-picture pairs; we used pattern classifiers, applied to fMRI data, to measure how strongly the picture associates were activating when participants were trying not to retrieve these associates, and we used a novel Bayesian curve-fitting procedure to relate this covert neural measure of retrieval to performance on a later memory test. In keeping with our hypothesis, the curve-fitting procedure revealed a nonmonotonic relationship between memory activation (as measured by the classifier) and subsequent memory, whereby moderate levels of activation of the to-be-suppressed item led to diminished performance on the final memory test, and higher levels of activation led to enhanced performance on the final test. PMID:23499722

Moderate levels of activation lead to forgetting in the think/no-think paradigm.

PubMed

Detre, Greg J; Natarajan, Annamalai; Gershman, Samuel J; Norman, Kenneth A

2013-10-01

Using the think/no-think paradigm (Anderson & Green, 2001), researchers have found that suppressing retrieval of a memory (in the presence of a strong retrieval cue) can make it harder to retrieve that memory on a subsequent test. This effect has been replicated numerous times, but the size of the effect is highly variable. Also, it is unclear from a neural mechanistic standpoint why preventing recall of a memory now should impair your ability to recall that memory later. Here, we address both of these puzzles using the idea, derived from computational modeling and studies of synaptic plasticity, that the function relating memory activation to learning is U-shaped, such that moderate levels of memory activation lead to weakening of the memory and higher levels of activation lead to strengthening. According to this view, forgetting effects in the think/no-think paradigm occur when the suppressed item activates moderately during the suppression attempt, leading to weakening; the effect is variable because sometimes the suppressed item activates strongly (leading to strengthening) and sometimes it does not activate at all (in which case no learning takes place). To test this hypothesis, we ran a think/no-think experiment where participants learned word-picture pairs; we used pattern classifiers, applied to fMRI data, to measure how strongly the picture associates were activating when participants were trying not to retrieve these associates, and we used a novel Bayesian curve-fitting procedure to relate this covert neural measure of retrieval to performance on a later memory test. In keeping with our hypothesis, the curve-fitting procedure revealed a nonmonotonic relationship between memory activation (as measured by the classifier) and subsequent memory, whereby moderate levels of activation of the to-be-suppressed item led to diminished performance on the final memory test, and higher levels of activation led to enhanced performance on the final test. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Journey Through and Beyond Mental Health Services in the United Kingdom: A Typology of Parents' Ways of Managing the Crisis of Their Teenage Child's Depression.

PubMed

Stapley, Emily; Target, Mary; Midgley, Nick

2017-10-01

Depression is a common mental illness experienced by young people. Yet we know little about how their parents manage their symptoms at home, and how parents may experience their treatment at child and adolescent mental health services (CAMHS). Thus, the aim of our study was to create a typology of parents' experiences over a 2-year period, beginning with their teenage child's referral to CAMHS in the United Kingdom. A total of 85 semistructured interviews were conducted with one or both parents of 28 adolescents at 3 time points, and qualitatively analyzed using ideal type analysis. Three distinct types or patterns of parental experience were identified: the learning curve parents, the finding my own solutions parents, the stuck parents. These patterns of parental experience could perhaps provide a basis for clinicians working in CAMHS to reflect on the families that they see and to adapt their ways of working accordingly to best support these families. © 2017 Wiley Periodicals, Inc.

HVM die yield improvement as a function of DRSEM ADC

NASA Astrophysics Data System (ADS)

Maheshwary, Sonu; Haas, Terry; McGarvey, Steve

2010-03-01

Given the current manufacturing technology roadmap and the competitiveness of the global semiconductor manufacturing environment in conjunction with the semiconductor manufacturing market dynamics, the market place continues to demand a reduced die manufacturing cost. This continuous pressure on lowering die cost in turn drives an aggressive yield learning curve, a key component of which is defect reduction of manufacturing induced anomalies. In order to meet and even exceed line and die yield targets there is a need to revamp defect classification strategies and place a greater emphasize on increasing the accuracy and purity of the Defect Review Scanning Electron Microscope (DRSEM) Automated Defect Classification (ADC) results while placing less emphasis on the ADC results of patterned/un-patterned wafer inspection systems. The increased emphasis on DRSEM ADC results allows for a high degree of automation and consistency in the classification data and eliminates variance induced by the manufacturing staff. This paper examines the use of SEM based Auto Defect Classification in a high volume manufacturing environment as a key driver in the reduction of defect limited yields.

Burial duration, depth and air pocket explain avalanche survival patterns in Austria and Switzerland.

PubMed

Procter, Emily; Strapazzon, Giacomo; Dal Cappello, Tomas; Zweifel, Benjamin; Würtele, Andreas; Renner, Andreas; Falk, Markus; Brugger, Hermann

2016-08-01

To calculate the first Austrian avalanche survival curve and update a Swiss survival curve to explore survival patterns in the Alps. Avalanche accidents occurring between 2005/06 and 2012/13 in Austria and Switzerland were collected. Completely buried victims (i.e. burial of the head and chest) in open terrain with known outcome (survived or not survived) were included in the analysis. Extrication and survival curves were calculated using the Turnbull algorithm, as in previous studies. 633 of the 796 completely buried victims were included (Austria n=333, Switzerland n=300). Overall survival was 56% (Austria 59%; Switzerland 52%; p=0.065). Time to extrication was shorter in Austria for victims buried ≤60min (p<0.001). The survival curves were similar and showed a rapid initial drop in survival probability and a second drop to 25-28% survival probability after burial duration of ca. 35min, where an inflection point exists and the curve levels off. In a logistic regression analysis, both duration of burial and burial depth had an independent effect on survival. Victims with an air pocket were more likely to survive, especially if buried >15min. The survival curves resembled those previously published and support the idea that underlying survival patterns are reproducible. The results are in accordance with current recommendations for management of avalanche victims and serve as a reminder that expedient companion rescue within a few minutes is critical for survival. An air pocket was shown to be a positive prognostic factor for survival. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Perceptual learning as improved probabilistic inference in early sensory areas.

PubMed

Bejjanki, Vikranth R; Beck, Jeffrey M; Lu, Zhong-Lin; Pouget, Alexandre

2011-05-01

Extensive training on simple tasks such as fine orientation discrimination results in large improvements in performance, a form of learning known as perceptual learning. Previous models have argued that perceptual learning is due to either sharpening and amplification of tuning curves in early visual areas or to improved probabilistic inference in later visual areas (at the decision stage). However, early theories are inconsistent with the conclusions of psychophysical experiments manipulating external noise, whereas late theories cannot explain the changes in neural responses that have been reported in cortical areas V1 and V4. Here we show that we can capture both the neurophysiological and behavioral aspects of perceptual learning by altering only the feedforward connectivity in a recurrent network of spiking neurons so as to improve probabilistic inference in early visual areas. The resulting network shows modest changes in tuning curves, in line with neurophysiological reports, along with a marked reduction in the amplitude of pairwise noise correlations.

Textbook Factor Demand Curves.

ERIC Educational Resources Information Center

Davis, Joe C.

1994-01-01

Maintains that teachers and textbook graphics follow the same basic pattern in illustrating changes in demand curves when product prices increase. Asserts that the use of computer graphics will enable teachers to be more precise in their graphic presentation of price elasticity. (CFR)

Motion patterns in acupuncture needle manipulation.

PubMed

Seo, Yoonjeong; Lee, In-Seon; Jung, Won-Mo; Ryu, Ho-Sun; Lim, Jinwoong; Ryu, Yeon-Hee; Kang, Jung-Won; Chae, Younbyoung

2014-10-01

In clinical practice, acupuncture manipulation is highly individualised for each practitioner. Before we establish a standard for acupuncture manipulation, it is important to understand completely the manifestations of acupuncture manipulation in the actual clinic. To examine motion patterns during acupuncture manipulation, we generated a fitted model of practitioners' motion patterns and evaluated their consistencies in acupuncture manipulation. Using a motion sensor, we obtained real-time motion data from eight experienced practitioners while they conducted acupuncture manipulation using their own techniques. We calculated the average amplitude and duration of a sampled motion unit for each practitioner and, after normalisation, we generated a true regression curve of motion patterns for each practitioner using a generalised additive mixed modelling (GAMM). We observed significant differences in rotation amplitude and duration in motion samples among practitioners. GAMM showed marked variations in average regression curves of motion patterns among practitioners but there was strong consistency in motion parameters for individual practitioners. The fitted regression model showed that the true regression curve accounted for an average of 50.2% of variance in the motion pattern for each practitioner. Our findings suggest that there is great inter-individual variability between practitioners, but remarkable intra-individual consistency within each practitioner. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Objective assessment of gynecologic laparoscopic skills using the LapSimGyn virtual reality simulator.

PubMed

Larsen, C R; Grantcharov, T; Aggarwal, R; Tully, A; Sørensen, J L; Dalsgaard, T; Ottesen, B

2006-09-01

Safe realistic training and unbiased quantitative assessment of technical skills are required for laparoscopy. Virtual reality (VR) simulators may be useful tools for training and assessing basic and advanced surgical skills and procedures. This study aimed to investigate the construct validity of the LapSimGyn VR simulator, and to determine the learning curves of gynecologists with different levels of experience. For this study, 32 gynecologic trainees and consultants (juniors or seniors) were allocated into three groups: novices (0 advanced laparoscopic procedures), intermediate level (>20 and <60 procedures), and experts (>100 procedures). All performed 10 sets of simulations consisting of three basic skill tasks and an ectopic pregnancy program. The simulations were carried out on 3 days within a maximum period of 2 weeks. Assessment of skills was based on time, economy of movement, and error parameters measured by the simulator. The data showed that expert gynecologists performed significantly and consistently better than intermediate and novice gynecologists. The learning curves differed significantly between the groups, showing that experts start at a higher level and more rapidly reach the plateau of their learning curve than do intermediate and novice groups of surgeons. The LapSimGyn VR simulator package demonstrates construct validity on both the basic skills module and the procedural gynecologic module for ectopic pregnancy. Learning curves can be obtained, but to reach the maximum performance for the more complex tasks, 10 repetitions do not seem sufficient at the given task level and settings. LapSimGyn also seems to be flexible and widely accepted by the users.

Learning curve of transumbilical single incision laparoscopic cholecystectomy (SILS): a preliminary study of 80 selected patients with benign gallbladder diseases.

PubMed

Qiu, Zhengjun; Sun, Jing; Pu, Ying; Jiang, Tao; Cao, Jun; Wu, Weidong

2011-09-01

Transumbilical single incision laparoscopic surgery (SILS) is a new laparoscopic procedure in which only one transumbilical incision is made, demonstrated as a scarless procedure. Here we report a single-center preliminary experience of transumbilical single incision laparoscopic cholecystectomy (SILC) in the treatment of benign gallbladder diseases, defining a single surgeon's learning curve. A total of 80 patients underwent SILC successfully by a single experienced laparoscopic surgeon. The operation was performed following the routine LC procedure. Then the perioperative demographics were recorded and the operative time was used to define the learning curve. The study group included 27 male and 53 female patients with gallstones (56 cases), cholesterol polyps (16 cases), an adenomatous polyp (3 cases), adenomyomatosis (1 case), or complex diseases (4 cases), and all consented to undergo SILC. No patient was converted to normal LC or open surgery. There were no perioperative port-related or surgical complications. The average operative time was 46.9 ± 14.6 min. The average postoperative hospital stay was 1.8 ± 1.3 days. The learning curve of the SILC procedures for this series of selected patients confirmed that SILC is a feasible, safe, and effective approach to the treatment of benign gallbladder diseases. For experienced laparoscopic surgeons, SILC is an easy and safe procedure. Patients benefit from milder pain, a lower incidence of port-related complications, better cosmesis, and fast recovery. The SILC procedure may become another option for the treatment of benign gallbladder diseases for selected patients.

Balloon dilation of the eustachian tube in a cadaver model: technical considerations, learning curve, and potential barriers.

PubMed

McCoul, Edward D; Singh, Ameet; Anand, Vijay K; Tabaee, Abtin

2012-04-01

The surgical management options for eustachian tube dysfunction have historically been limited. The goal of the current study was to evaluate the technical considerations, learning curve, and potential barriers for balloon dilation of the eustachian tube (BDET) as an alternative treatment modality. Prospective preclinical trial of BDET in a cadaver model. A novel balloon catheter device was used for eustachian tube dilation. Twenty-four BDET procedures were performed by three independent rhinologists with no prior experience with the procedure (eight procedures per surgeon). The duration and number of attempts of the individual steps and overall procedure were recorded. Endoscopic examination of the eustachian tube was performed after each procedure, and the surgeon was asked to rate the subjective difficulty on a five-point scale. Successful completion of the procedure occurred in each case. The overall mean duration of the procedure was 284 seconds, and a mean number of 1.15 attempts were necessary to perform the individual steps. The mean subjective procedure difficulty was noted as somewhat easy. Statistically shorter duration and subjectively easier procedure were noted in the second compared to the first half of the series, indicating a favorable learning curve. Linear fissuring within the eustachian tube lumen without submucosal disruption (nine procedures, 37%) and with submucosal disruption (five procedures, 21%) were noted. The significance of these physical findings is unclear. Preclinical testing of BDET is associated with favorable duration, learning curve, and overall ease of completion. Clinical trials are necessary to evaluate safety and efficacy. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

Venous Grafts Procured During the Learning Curve for Endoscopic Veins Harvesting Show Compromised Vascular Remodeling

PubMed Central

Kiani, Soroosh; Desai, Pranjal H.; Thirumvalavan, Nannan; Kurian, Dinesh John; Flynn, Mary Margaret; Zhao, XiaoQing

2011-01-01

BACKGROUND Endoscopic vein harvest (EVH) is the US standard of care for CABG but recent comparisons to open harvest suggest that conduit quality and outcomes may be compromised. To test the hypothesis that problems with EVH may relate to its learning curve and conduit quality, we analyzed the quality and early function of conduits procured by technicians with varying EVH experience. METHODS EVH was performed during CABG by “experienced” (>900 cases, n=55 patients) vs. “novice” (<100 cases, n=30 patients) technicians. Afterwards, conduits were and examined for vascular injury using optical coherence tomography (OCT), with segments identified as injured further examined for gene expression using a tissue injury array. Conduit diameter was measured intra- and postoperatively (day 5 and 6 months) using OCT and Computed-Tomography angiography. RESULTS EVH performed by novice harvesters resulted in increased number of discrete graft injuries and higher expression of tissue injury genes. Regression analysis revealed an association between shear stress and early dilation (positive remodeling) (R2 =0.48, p <0.01). Injured veins showed blunted positive remodeling at 5 days and a greater degree of late lumen loss at 6 months. CONCLUSION Under normal conditions, intraluminal shear stress leads vein grafts to develop positive remodeling over the first postoperative week. Injury to conduits, a frequent sequela of the learning curve for EVH, was a predictor of early graft failure, blunted positive remodeling and greater negative remodeling. Given the ongoing annual volume of EVH cases, rigorous monitoring of the learning curve represents an important and unrecognized public health issue. PMID:21996436

Transanal total mesorectal excision for rectal cancer: evaluation of the learning curve.

PubMed

Koedam, T W A; Veltcamp Helbach, M; van de Ven, P M; Kruyt, Ph M; van Heek, N T; Bonjer, H J; Tuynman, J B; Sietses, C

2018-04-01

Transanal total mesorectal excision (TaTME) provides an excellent view of the resection margins for rectal cancer from below, but is challenging due to few anatomical landmarks. During implementation of this technique, patient safety and optimal outcomes need to be ensured. The aim of this study was to evaluate the learning curve of TaTME in patients with rectal cancer in order to optimize future training programs. All consecutive patients after TaTME for rectal cancer between February 2012 and January 2017 were included in a single-center database. Influence of surgical experience on major postoperative complications, leakage rate and operating time was evaluated using cumulative sum charts and the splitting model. Correction for potential case-mix differences was performed. Over a period of 60 months, a total of 138 patients were included in this study. Adjusted for case-mix, improvement in postoperative outcomes was clearly seen after the first 40 patients, showing a decrease in major postoperative complications from 47.5 to 17.5% and leakage rate from 27.5 to 5%. Mean operating time (42 min) and conversion rate (from 10% to zero) was lower after transition to a two-team approach, but neither endpoint decreased with experience. Readmission and reoperation rates were not influenced by surgical experience. The learning curve of TaTME affected major (surgical) postoperative complications for the first 40 patients. A two-team approach decreased operative time and conversion rate. When implementing this new technique, a thorough teaching and supervisory program is recommended to shorten the learning curve and improve the clinical outcomes of the first patients.

Adoption of Robotic vs Fluoroscopic Guidance in Total Hip Arthroplasty: Is Acetabular Positioning Improved in the Learning Curve?

PubMed

Kamara, Eli; Robinson, Jonathon; Bas, Marcel A; Rodriguez, Jose A; Hepinstall, Matthew S

2017-01-01

Acetabulum positioning affects dislocation rates, component impingement, bearing surface wear rates, and need for revision surgery. Novel techniques purport to improve the accuracy and precision of acetabular component position, but may have a significant learning curve. Our aim was to assess whether adopting robotic or fluoroscopic techniques improve acetabulum positioning compared to manual total hip arthroplasty (THA) during the learning curve. Three types of THAs were compared in this retrospective cohort: (1) the first 100 fluoroscopically guided direct anterior THAs (fluoroscopic anterior [FA]) done by a surgeon learning the anterior approach, (2) the first 100 robotic-assisted posterior THAs done by a surgeon learning robotic-assisted surgery (robotic posterior [RP]), and (3) the last 100 manual posterior (MP) THAs done by each surgeon (200 THAs) before adoption of novel techniques. Component position was measured on plain radiographs. Radiographic measurements were taken by 2 blinded observers. The percentage of hips within the surgeons' "target zone" (inclination, 30°-50°; anteversion, 10°-30°) was calculated, along with the percentage within the "safe zone" of Lewinnek (inclination, 30°-50°; anteversion, 5°-25°) and Callanan (inclination, 30°-45°; anteversion, 5°-25°). Relative risk (RR) and absolute risk reduction (ARR) were calculated. Variances (square of the standard deviations) were used to describe the variability of cup position. Seventy-six percentage of MP THAs were within the surgeons' target zone compared with 84% of FA THAs and 97% of RP THAs. This difference was statistically significant, associated with a RR reduction of 87% (RR, 0.13 [0.04-0.40]; P < .01; ARR, 21%; number needed to treat, 5) for RP compared to MP THAs. Compared to FA THAs, RP THAs were associated with a RR reduction of 81% (RR, 0.19 [0.06-0.62]; P < .01; ARR, 13%; number needed to treat, 8). Variances were lower for acetabulum inclination and anteversion in RP THAs (14.0 and 19.5) as compared to the MP (37.5 and 56.3) and FA (24.5 and 54.6) groups. These differences were statistically significant (P < .01). Adoption of robotic techniques delivers significant and immediate improvement in the precision of acetabular component positioning during the learning curve. While fluoroscopy has been shown to be beneficial with experience, a learning curve exists before precision improves significantly. Copyright © 2016 Elsevier Inc. All rights reserved.

A Glance at Institutional Support for Faculty Teaching in an Online Learning Environment

ERIC Educational Resources Information Center

Lion, Robert W.; Stark, Gary

2010-01-01

With continued advances in web-based learning, colleges and universities strive to meet the needs and interests of students, faculty, and staff. New instructional technologies have at least one thing in common: the learning curve associated with users becoming adept. Mastery requires significant time and attention. Providing the best quality…

Curved Saccade Trajectories Reveal Conflicting Predictions in Associative Learning

ERIC Educational Resources Information Center

Koenig, Stephan; Lachnit, Harald

2011-01-01

We report how the trajectories of saccadic eye movements are affected by memory interference acquired during associative learning. Human participants learned to perform saccadic choice responses based on the presentation of arbitrary central cues A, B, AC, BC, AX, BY, X, and Y that were trained to predict the appearance of a peripheral target…

Verbal Knowledge, Working Memory, and Processing Speed as Predictors of Verbal Learning in Older Adults

ERIC Educational Resources Information Center

Rast, Philippe

2011-01-01

The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables--speed of information processing, verbal knowledge, working…

Motor learning in childhood reveals distinct mechanisms for memory retention and re-learning.

PubMed

Musselman, Kristin E; Roemmich, Ryan T; Garrett, Ben; Bastian, Amy J

2016-05-01

Adults can easily learn and access multiple versions of the same motor skill adapted for different conditions (e.g., walking in water, sand, snow). Following even a single session of adaptation, adults exhibit clear day-to-day retention and faster re-learning of the adapted pattern. Here, we studied the retention and re-learning of an adapted walking pattern in children aged 6-17 yr. We found that all children, regardless of age, showed adult-like patterns of retention of the adapted walking pattern. In contrast, children under 12 yr of age did not re-learn faster on the next day after washout had occurred-they behaved as if they had never adapted their walking before. Re-learning could be improved in younger children when the adaptation time on day 1 was increased to allow more practice at the plateau of the adapted pattern, but never to adult-like levels. These results show that the ability to store a separate, adapted version of the same general motor pattern does not fully develop until adolescence, and furthermore, that the mechanisms underlying the retention and rapid re-learning of adapted motor patterns are distinct. © 2016 Musselman et al.; Published by Cold Spring Harbor Laboratory Press.

MILS in a general surgery unit: learning curve, indications, and limitations.

PubMed

Patriti, Alberto; Marano, Luigi; Casciola, Luciano

2015-06-01

Minimally invasive liver surgery (MILS) is going to be a method with a wide diffusion even in general surgery units. Organization, learning curve effect, and the environment are crucial issues to evaluate before starting a program of minimally invasive liver resections. Analysis of a consecutive series of 70 patients has been used to define advantages and limits of starting a program of MILS in a general surgery unit. Seventeen MILS have been calculated with the cumulative sum method as the number of cases to complete the learning curve. Operative times [270 (60-480) vs. 180 (15-550) min; p 0.01] and rate of conversion (6/17 vs. 5/53; p 0.018) decrease after this number of cases. More complex cases can be managed after a proper optimization of all steps of liver resection. When a high confidence of the medical and nurse staff with MILS is reached, economical and strategic issues should be evaluated in order to establish a multidisciplinary hepatobiliary unit independent from the general surgery unit to manage more complex cases.

Measuring the surgical 'learning curve': methods, variables and competency.

PubMed

Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

2014-03-01

To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

Modeling cascading diffusion of new energy technologies: case study of residential solid oxide fuel cells in the US and internationally.

PubMed

Herron, Seth; Williams, Eric

2013-08-06

Subsidy programs for new energy technologies are motivated by the experience curve: increased adoption of a technology leads to learning and economies of scale that lower costs. Geographic differences in fuel prices and climate lead to large variability in the economic performance of energy technologies. The notion of cascading diffusion is that regions with favorable economic conditions serve as the basis to build scale and reduce costs so that the technology becomes attractive in new regions. We develop a model of cascading diffusion and implement via a case study of residential solid oxide fuel cells (SOFCs) for combined heating and power. We consider diffusion paths within the U.S. and internationally. We construct market willingness-to-pay curves and estimate future manufacturing costs via an experience curve. Combining market and cost results, we find that for rapid cost reductions (learning rate = 25%), a modest public subsidy can make SOFC investment profitable for 20-160 million households. If cost reductions are slow however (learning rate = 15%), residential SOFCs may not become economically competitive. Due to higher energy prices in some countries, international diffusion is more favorable than domestic, mitigating much of the uncertainty in the learning rate.

Centrifugal fingering in a curved Hele-Shaw cell: A generalized Euler's elastica shape for the two-fluid interface

NASA Astrophysics Data System (ADS)

Miranda, Jose; Brandao, Rodolfo

2017-11-01

We study a family of generalized elastica-like equilibrium shapes that arise at the interface separating two fluids in a curved rotating Hele-Shaw cell. This family of stationary interface solutions consists of shapes that balance the competing capillary and centrifugal forces in such a curved flow environment. We investigate how the emerging interfacial patterns are impacted by changes in the geometric properties of the curved Hele-Shaw cell. A vortex-sheet formalism is used to calculate the two-fluid interface curvature, and a gallery of possible shapes is provided to highlight a number of peculiar morphological features. A linear perturbation theory is employed to show that the most prominent aspects of these complex stationary patterns can be fairly well reproduced by the interplay of just two interfacial modes. The connection of these dominant modes to the geometry of the curved cell, as well as to the fluid dynamic properties of the flow, is discussed. We thank CNPq (Brazilian Research Council) for financial support under Grant No. 304821/2015-2.

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lochner, Michelle; Peiris, Hiranya V.; Lahav, Ofer

Automated photometric supernova classification has become an active area of research in recent years in light of current and upcoming imaging surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope, given that spectroscopic confirmation of type for all supernovae discovered will be impossible. Here, we develop a multi-faceted classification pipeline, combining existing and new approaches. Our pipeline consists of two stages: extracting descriptive features from the light curves and classification using a machine learning algorithm. Our feature extraction methods vary from model-dependent techniques, namely SALT2 fits, to more independent techniques that fit parametric models tomore » curves, to a completely model-independent wavelet approach. We cover a range of representative machine learning algorithms, including naive Bayes, k -nearest neighbors, support vector machines, artificial neural networks, and boosted decision trees (BDTs). We test the pipeline on simulated multi-band DES light curves from the Supernova Photometric Classification Challenge. Using the commonly used area under the curve (AUC) of the Receiver Operating Characteristic as a metric, we find that the SALT2 fits and the wavelet approach, with the BDTs algorithm, each achieve an AUC of 0.98, where 1 represents perfect classification. We find that a representative training set is essential for good classification, whatever the feature set or algorithm, with implications for spectroscopic follow-up. Importantly, we find that by using either the SALT2 or the wavelet feature sets with a BDT algorithm, accurate classification is possible purely from light curve data, without the need for any redshift information.« less

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

PubMed

Lin, Frank Po-Yen; Pokorny, Adrian; Teng, Christina; Epstein, Richard J

2017-07-31

Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical narratives, we have built a novel computational pipeline termed Text-based Exploratory Pattern Analyser for Prognosticator and Associator discovery (TEPAPA). This pipeline combines semantic-free natural language processing (NLP), regular expression induction, and statistical association testing to identify conserved text patterns associated with outcome variables of clinical interest. When we applied TEPAPA to a cohort of head and neck squamous cell carcinoma patients, plausible concepts known to be correlated with human papilloma virus (HPV) status were identified from the EMR text, including site of primary disease, tumour stage, pathologic characteristics, and treatment modalities. Similarly, correlates of other variables (including gender, nodal status, recurrent disease, smoking and alcohol status) were also reliably recovered. Using highly-associated patterns as covariates, a patient's HPV status was classifiable using a bootstrap analysis with a mean area under the ROC curve of 0.861, suggesting its predictive utility in supporting EMR-based phenotyping tasks. These data support using this integrative approach to efficiently identify disease-associated factors from unstructured EMR narratives, and thus to efficiently generate testable hypotheses.

Learning New Letter-like Writing Patterns Explicitly and Implicitly in Children and Adults.

PubMed

Jongbloed-Pereboom, M; Overvelde, A; Nijhuis-van der Sanden, M W G; Steenbergen, B

2017-12-15

A handwriting task was used to test the assumption that explicit learning is dependent on age and working memory, while implicit learning is not. The effect of age was examined by testing both, typically developing children (5-12 years old, n = 81) and adults (n = 27) in a counterbalanced within-subjects design. Participants were asked to repeatedly write letter-like patterns on a digitizer with a non-inking pen. Reproduction of the pattern was better after explicit learning compared to implicit learning. Age had positive effects on both explicit and implicit learning; working memory did not affect learning in either conditions. These results show that it may be more effective to learn writing new letter-like patterns explicitly and that an explicit teaching method is preferred in mainstream primary education.

Hilbert-Curve Fractal Antenna With Radiation- Pattern Diversity

NASA Technical Reports Server (NTRS)

Nessel, James A.; Miranda, Felix A.; Zaman, Afroz

2007-01-01

A printed, folded, Hilbert-curve fractal microwave antenna has been designed and built to offer advantages of compactness and low mass, relative to other antennas designed for the same operating frequencies. The primary feature of the antenna is that it offers the advantage of radiation-pattern diversity without need for electrical or mechanical switching: it can radiate simultaneously in an end-fire pattern at a frequency of 2.3 GHz (which is in the S-band) and in a broadside pattern at a frequency of 16.8 GHz (which is in the Ku-band). This radiation-pattern diversity could be utilized, for example, in applications in which there were requirements for both S-band ground-to-ground communications and Ku-band ground-to-aircraft or ground-to-spacecraft communications. The lack of switching mechanisms or circuitry makes this antenna more reliable, easier, and less expensive to fabricate than it otherwise would be.

Exploring Learners' Sequential Behavioral Patterns, Flow Experience, and Learning Performance in an Anti-Phishing Educational Game

ERIC Educational Resources Information Center

Sun, Jerry Chih-Yuan; Kuo, Cian-Yu; Hou, Huei-Tse; Lin, Yu-Yan

2017-01-01

The purposes of this study were to provide a game-based anti-phishing lesson to 110 elementary school students in Taiwan, explore their learning behavioral patterns, and investigate the effects of the flow states on their learning behavioral patterns and learning achievement. The study recorded behaviour logs, and applied a pre- and post-test on…

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Marangoni-induced symmetry-breaking pattern selection on viscous fluids

NASA Astrophysics Data System (ADS)

Shen, Li; Denner, Fabian; Morgan, Neal; van Wachem, Berend; Dini, Daniele

2016-11-01

Symmetry breaking transitions on curved surfaces are found in a wide range of dissipative systems, ranging from asymmetric cell divisions to structure formation in thin films. Inherent within the nonlinearities are the associated curvilinear geometry, the elastic stretching, bending and the various fluid dynamical processes. We present a generalised Swift-Hohenberg pattern selection theory on a thin, curved and viscous films in the presence of non-trivial Marangoni effect. Testing the theory with experiments on soap bubbles, we observe the film pattern selection to mimic that of the elastic wrinkling morphology on a curved elastic bilayer in regions of slow viscous flow. By examining the local state of damping of surface capillary waves we attempt to establish an equivalence between the Marangoni fluid dynamics and the nonlinear elastic shell theory above the critical wavenumber of the instabilities and propose a possible explanation for the perceived elastic-fluidic duality. The authors acknowledge the financial support of the Shell University Technology Centre for fuels and lubricants.

Differential survivorship among allozyme genotypes of Hyalella azteca exposed to cadmium, zinc or low pH.

PubMed

Duan, Y; Guttman, S I; Oris, J T; Bailer, A J

2001-09-01

The survival functions (SF) during acute exposures to cadmium, zinc or low pH were examined for amphipods exhibiting variation at three loci. Significant differences were observed in eight of nine locus/toxicant combinations. Two general types of survival curve patterns were identified when genotype-related SF differences were observed. In the first pattern, the survival differences between genotypes were immediately apparent with two SF curves separated at the beginning of exposure with little or no overlap. For the second pattern, both genotypes had similar SF for a period of time, during which the two survival curves crossed or overlapped. After this period, the survival probability of one genotype dropped sharply relative to the other. While SF was related to genotype, it was not related to heterozygosity. Genetic distance analysis showed that exposure to cadmium, zinc or low pH each resulted in directional selection, suggesting the potential use of genetic distance as a bioindicator.

Amnesia, rehearsal, and temporal distinctiveness models of recall.

PubMed

Brown, Gordon D A; Della Sala, Sergio; Foster, Jonathan K; Vousden, Janet I

2007-04-01

Classical amnesia involves selective memory impairment for temporally distant items in free recall (impaired primacy) together with relative preservation of memory for recency items. This abnormal serial position curve is traditionally taken as evidence for a distinction between different memory processes, with amnesia being associated with selectively impaired long-term memory. However recent accounts of normal serial position curves have emphasized the importance of rehearsal processes in giving rise to primacy effects and have suggested that a single temporal distinctiveness mechanism can account for both primacy and recency effects when rehearsal is considered. Here we explore the pattern of strategic rehearsal in a patient with very severe amnesia. When the patient's rehearsal pattern is taken into account, a temporal distinctiveness model can account for the serial position curve in both amnesic and control free recall. The results are taken as consistent with temporal distinctiveness models of free recall, and they motivate an emphasis on rehearsal patterns in understanding amnesic deficits in free recall.

Ten years in the library: new data confirm paleontological patterns

NASA Technical Reports Server (NTRS)

Sepkoski, J. J. Jr; Sepkoski JJ, J. r. (Principal Investigator)

1993-01-01

A comparison is made between compilations of times of origination and extinction of fossil marine animal families published in 1982 and 1992. As a result of ten years of library research, half of the information in the compendia has changed: families have been added and deleted, low-resolution stratigraphic data been improved, and intervals of origination and extinction have been altered. Despite these changes, apparent macroevolutionary patterns for the entire marine fauna have remained constant. Diversity curves compiled from the two data bases are very similar, with a goodness-of-fit of 99%; the principal difference is that the 1992 curve averages 13% higher than the older curve. Both numbers and percentages of origination and extinction also match well, with fits ranging from 83% to 95%. All major events of radiation and extinction are identical. Therefore, errors in large paleontological data bases and arbitrariness of included taxa are not necessarily impediments to the analysis of pattern in the fossil record, so long as the data are sufficiently numerous.

The Implications of Null Patterns and Output Unit Activation Functions on Simulation Studies of Learning: A Case Study of Patterning

ERIC Educational Resources Information Center

Yaremchuk, V.; Willson, L.R.; Spetch, M.L.; Dawson, M.R.W.

2005-01-01

Animal learning researchers have argued that one example of a linearly nonseparable problem is negative patterning, and therefore they have used more complicated multilayer networks to study this kind of discriminant learning. However, it is shown in this paper that previous attempts to define negative patterning problems to artificial neural…

Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study.

PubMed

Oh, Ein; Yoo, Tae Keun; Park, Eun-Cheol

2013-09-13

Blindness due to diabetic retinopathy (DR) is the major disability in diabetic patients. Although early management has shown to prevent vision loss, diabetic patients have a low rate of routine ophthalmologic examination. Hence, we developed and validated sparse learning models with the aim of identifying the risk of DR in diabetic patients. Health records from the Korea National Health and Nutrition Examination Surveys (KNHANES) V-1 were used. The prediction models for DR were constructed using data from 327 diabetic patients, and were validated internally on 163 patients in the KNHANES V-1. External validation was performed using 562 diabetic patients in the KNHANES V-2. The learning models, including ridge, elastic net, and LASSO, were compared to the traditional indicators of DR. Considering the Bayesian information criterion, LASSO predicted DR most efficiently. In the internal and external validation, LASSO was significantly superior to the traditional indicators by calculating the area under the curve (AUC) of the receiver operating characteristic. LASSO showed an AUC of 0.81 and an accuracy of 73.6% in the internal validation, and an AUC of 0.82 and an accuracy of 75.2% in the external validation. The sparse learning model using LASSO was effective in analyzing the epidemiological underlying patterns of DR. This is the first study to develop a machine learning model to predict DR risk using health records. LASSO can be an excellent choice when both discriminative power and variable selection are important in the analysis of high-dimensional electronic health records.

Stimulus dependent neural oscillatory patterns show reliable statistical identification of autism spectrum disorder in a face perceptual decision task.

PubMed

Castelhano, João; Tavares, Paula; Mouga, Susana; Oliveira, Guiomar; Castelo-Branco, Miguel

2018-05-01

Electroencephalographic biomarkers have been widely investigated in autism, in the search for diagnostic, prognostic and therapeutic outcome measures. Here we took advantage of the information available in temporal oscillatory patterns evoked by simple perceptual decisions to investigate whether stimulus dependent oscillatory signatures can be used as potential biomarkers in autism spectrum disorder (ASD). We studied an extensive set of stimuli (9 categories of faces) and performed data driven classification (Support vector machine, SVM) of ASD vs. Controls with features based on the EEG power responses. We carried out an extensive time-frequency and synchrony analysis of distinct face categories requiring different processing mechanisms in terms of non-holistic vs. holistic processing. We found that the neuronal oscillatory responses of low gamma frequency band, locked to photographic and abstract two-tone (Mooney) face stimulus presentation are decreased in ASD vs. the control group. We also found decreased time-frequency (TF) responses in the beta band in ASD after 350 ms, possibly related to motor preparation. On the other hand, synchrony in the 30-45 Hz band showed a distinct spatial pattern in ASD. These power changes enabled accurate classification of ASD with an SVM approach. SVM accuracy was approximately 85%. ROC curves showed about 94% AUC (area under the curve). Combination of Mooney and Photographic face stimuli evoked features enabled a better separation between groups, reaching an AUC of 98.6%. We identified a relative decrease in EEG responses to face stimuli in ASD in the beta (15-30 Hz; >350 ms) and gamma (30-45 Hz; 55-80 Hz; 50-350 ms) frequency ranges. These can be used as input of a machine learning approach to separate between groups with high accuracy. Future studies can use EEG time-frequency patterns evoked by particular types of faces as a diagnostic biomarker and potentially as outcome measures in therapeutic trials. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Infrared rotational light curves on Jupiter induced by wave activities and cloud patterns andimplications on brown dwarfs

NASA Astrophysics Data System (ADS)

Ge, Huazhi; Zhang, Xi; Fletcher, Leigh; Orton, Glenn S.; Sinclair, James Andrew; Fernandes,, Joshua; Momary, Thomas W.; Warren, Ari; Kasaba, Yasumasa; Sato, Takao M.; Fujiyoshi, Takuya

2017-10-01

Many brown dwarfs exhibit infrared rotational light curves with amplitude varying from a fewpercent to twenty percent (Artigau et al. 2009, ApJ, 701, 1534; Radigan et al. 2012, ApJ, 750,105). Recently, it was claimed that weather patterns, especially planetary-scale waves in thebelts and cloud spots, are responsible for the light curves and their evolutions on brown dwarfs(Apai et al. 2017, Science, 357, 683). Here we present a clear relationship between the direct IRemission maps and light curves of Jupiter at multiple wavelengths, which might be similar withthat on cold brown dwarfs. Based on infrared disk maps from Subaru/COMICS and VLT/VISIR,we constructed full maps of Jupiter and rotational light curves at different wavelengths in thethermal infrared. We discovered a strong relationship between the light curves and weatherpatterns on Jupiter. The light curves also exhibit strong multi-bands phase shifts and temporalvariations, similar to that detected on brown dwarfs. Together with the spectra fromTEXES/IRTF, our observations further provide detailed information of the spatial variations oftemperature, ammonia clouds and aerosols in the troposphere of Jupiter (Fletcher et al. 2016,Icarus, 2016 128) and their influences on the shapes of the light curves. We conclude that waveactivities in Jupiter’s belts (Fletcher et al. 2017, GRL, 44, 7140), cloud holes, and long-livedvortices such as the Great Red Spot and ovals control the shapes of IR light curves and multi-wavelength phase shifts on Jupiter. Our finding supports the hypothesis that observed lightcurves on brown dwarfs are induced by planetary-scale waves and cloud spots.

Training anesthesiology residents in providing anesthesia for awake craniotomy: learning curves and estimate of needed case load.

PubMed

Bilotta, Federico; Titi, Luca; Lanni, Fabiana; Stazi, Elisabetta; Rosa, Giovanni

2013-08-01

To measure the learning curves of residents in anesthesiology in providing anesthesia for awake craniotomy, and to estimate the case load needed to achieve a "good-excellent" level of competence. Prospective study. Operating room of a university hospital. 7 volunteer residents in anesthesiology. Residents underwent a dedicated training program of clinical characteristics of anesthesia for awake craniotomy. The program was divided into three tasks: local anesthesia, sedation-analgesia, and intraoperative hemodynamic management. The learning curve for each resident for each task was recorded over 10 procedures. Quantitative assessment of the individual's ability was based on the resident's self-assessment score and the attending anesthesiologist's judgment, and rated by modified 12 mm Likert scale, reported ability score visual analog scale (VAS). This ability VAS score ranged from 1 to 12 (ie, very poor, mild, moderate, sufficient, good, excellent). The number of requests for advice also was recorded (ie, resident requests for practical help and theoretical notions to accomplish the procedures). Each task had a specific learning rate; the number of procedures necessary to achieve "good-excellent" ability with confidence, as determined by the recorded results, were 10 procedures for local anesthesia, 15 to 25 procedures for sedation-analgesia, and 20 to 30 procedures for intraoperative hemodynamic management. Awake craniotomy is an approach used increasingly in neuroanesthesia. A dedicated training program based on learning specific tasks and building confidence with essential features provides "good-excellent" ability. © 2013 Elsevier Inc. All rights reserved.

Multi-q pattern classification of polarization curves

NASA Astrophysics Data System (ADS)

Fabbri, Ricardo; Bastos, Ivan N.; Neto, Francisco D. Moura; Lopes, Francisco J. P.; Gonçalves, Wesley N.; Bruno, Odemir M.

2014-02-01

Several experimental measurements are expressed in the form of one-dimensional profiles, for which there is a scarcity of methodologies able to classify the pertinence of a given result to a specific group. The polarization curves that evaluate the corrosion kinetics of electrodes in corrosive media are applications where the behavior is chiefly analyzed from profiles. Polarization curves are indeed a classic method to determine the global kinetics of metallic electrodes, but the strong nonlinearity from different metals and alloys can overlap and the discrimination becomes a challenging problem. Moreover, even finding a typical curve from replicated tests requires subjective judgment. In this paper, we used the so-called multi-q approach based on the Tsallis statistics in a classification engine to separate the multiple polarization curve profiles of two stainless steels. We collected 48 experimental polarization curves in an aqueous chloride medium of two stainless steel types, with different resistance against localized corrosion. Multi-q pattern analysis was then carried out on a wide potential range, from cathodic up to anodic regions. An excellent classification rate was obtained, at a success rate of 90%, 80%, and 83% for low (cathodic), high (anodic), and both potential ranges, respectively, using only 2% of the original profile data. These results show the potential of the proposed approach towards efficient, robust, systematic and automatic classification of highly nonlinear profile curves.

Image-based spectroscopy for environmental monitoring

NASA Astrophysics Data System (ADS)

Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

2014-03-01

An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

Temperature and field direction dependences of first-order reversal curve (FORC) diagrams of hot-deformed Nd-Fe-B magnets

NASA Astrophysics Data System (ADS)

Yomogita, Takahiro; Okamoto, Satoshi; Kikuchi, Nobuaki; Kitakami, Osamu; Sepehri-Amin, Hossein; Ohkubo, Tadakatsu; Hono, Kazuhiro; Akiya, Takahiro; Hioki, Keiko; Hattori, Atsushi

2018-02-01

First-order reversal curve (FORC) diagram has been previously adopted for the analyses of magnetization reversal process and/or quantitative evaluation of coercivity and interaction field dispersions in various magnetic samples. Although these kinds of information are valuable for permanent magnets, previously reported FORC diagrams of sintered Nd-Fe-B magnets exhibit very complicated patterns. In this paper, we have studied the FORC diagrams of hot-deformed Nd-Fe-B magnets under various conditions. Contrary to the previous reports on sintered Nd-Fe-B magnets, the FORC diagram of the hot-deformed Nd-Fe-B magnet exhibits a very simple pattern consisting of a strong spot and a weak line. From this FORC diagram pattern, it is revealed that the coercivity dispersion of the hot-deformed Nd-Fe-B magnets is surprisingly small. Moreover, this feature of the FORC diagram pattern is very robust and unaffected by changes in various conditions such as grain boundary diffusion process, temperature, and field direction, whereas these conditions significantly change the coercivity and the shape of magnetization curve. This fact indicates that the magnetization reversal process of the hot-deformed Nd-Fe-B magnets is almost unchanged against these conditions.

The Multigroup Multilevel Categorical Latent Growth Curve Models

ERIC Educational Resources Information Center

Hung, Lai-Fa

2010-01-01

Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…

What Is the Future of Learning in Canada?

ERIC Educational Resources Information Center

Canadian Council on Learning, 2011

2011-01-01

In its final report to Canadians, the Canadian Council on Learning (CCL) reveals that Canada is slipping down the international learning curve. The needs in this area are stark. The potential rewards are enormous. But Canada is falling behind competitor countries and economies. It is on the wrong road and must make a dramatic change in the course…

Learning Curve Analyses in Neurodevelopmental Disorders: Are Children with Autism Spectrum Disorder Truly Visual Learners?

ERIC Educational Resources Information Center

Erdodi, Laszlo; Lajiness-O'Neill, Renee; Schmitt, Thomas A.

2013-01-01

Visual and auditory verbal learning using a selective reminding format was studied in a mixed clinical sample of children with autism spectrum disorder (ASD) (n = 42), attention-deficit hyperactivity disorder (n = 83), velocardiofacial syndrome (n = 17) and neurotypicals (n = 38) using the Test of Memory and Learning to (1) more thoroughly…

Classification of optical coherence tomography images for diagnosing different ocular diseases

NASA Astrophysics Data System (ADS)

Gholami, Peyman; Sheikh Hassani, Mohsen; Kuppuswamy Parthasarathy, Mohana; Zelek, John S.; Lakshminarayanan, Vasudevan

2018-03-01

Optical Coherence tomography (OCT) images provide several indicators, e.g., the shape and the thickness of different retinal layers, which can be used for various clinical and non-clinical purposes. We propose an automated classification method to identify different ocular diseases, based on the local binary pattern features. The database consists of normal and diseased human eye SD-OCT images. We use a multiphase approach for building our classifier, including preprocessing, Meta learning, and active learning. Pre-processing is applied to the data to handle missing features from images and replace them with the mean or median of the corresponding feature. All the features are run through a Correlation-based Feature Subset Selection algorithm to detect the most informative features and omit the less informative ones. A Meta learning approach is applied to the data, in which a SVM and random forest are combined to obtain a more robust classifier. Active learning is also applied to strengthen our classifier around the decision boundary. The primary experimental results indicate that our method is able to differentiate between the normal and non-normal retina with an area under the ROC curve (AUC) of 98.6% and also to diagnose the three common retina-related diseases, i.e., Age-related Macular Degeneration, Diabetic Retinopathy, and Macular Hole, with an AUC of 100%, 95% and 83.8% respectively. These results indicate a better performance of the proposed method compared to most of the previous works in the literature.

Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

PubMed Central

Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2018-01-01

Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven labelers. We also compared the performance of the passive and active learning models when using the consensus label. Results The AL methods produced, for the models induced from each labeler, smoother Intra-labeler learning curves during the training phase, compared to the models produced when using the passive learning method. The mean standard deviation of the learning curves of the three AL methods over all labelers (mean: 0.0379; range: [0.0182 to 0.0496]), was significantly lower (p = 0.049) than the Intra-labeler standard deviation when using the passive learning method (mean: 0.0484; range: [0.0275 to 0.0724). Using the AL methods resulted in a lower mean Inter-labeler AUC standard deviation among the AUC values of the labelers’ different models during the training phase, compared to the variance of the induced models’ AUC values when using passive learning. The Inter-labeler AUC standard deviation, using the passive learning method (0.039), was almost twice as high as the Inter-labeler standard deviation using our two new AL methods (0.02 and 0.019, respectively). The SVM-Margin AL method resulted in an Inter-labeler standard deviation (0.029) that was higher by almost 50% than that of our two AL methods. The difference in the inter-labeler standard deviation between the passive learning method and the SVM-Margin learning method was significant (p = 0.042). The difference between the SVM-Margin and Exploitation method was insignificant (p = 0.29), as was the difference between the Combination_XA and Exploitation methods (p = 0.67). Finally, using the consensus label led to a learning curve that had a higher mean intra-labeler variance, but resulted eventually in an AUC that was at least as high as the AUC achieved using the gold standard label and that was always higher than the expected mean AUC of a randomly selected labeler, regardless of the choice of learning method (including a passive learning method). Using a paired t-test, the difference between the intra-labeler AUC standard deviation when using the consensus label, versus that value when using the other two labeling strategies, was significant only when using the passive learning method (p = 0.014), but not when using any of the three AL methods. Conclusions The use of AL methods, (a) reduces intra-labeler variability in the performance of the induced models during the training phase, and thus reduces the risk of halting the process at a local minimum that is significantly different in performance from the rest of the learned models; and (b) reduces Inter-labeler performance variance, and thus reduces the dependence on the use of a particular labeler. In addition, the use of a consensus label, agreed upon by a rather uneven group of labelers, might be at least as good as using the gold standard labeler, who might not be available, and certainly better than randomly selecting one of the group’s individual labelers. Finally, using the AL methods when provided by the consensus label reduced the intra-labeler AUC variance during the learning phase, compared to using passive learning. PMID:28456512

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

PubMed

Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

2017-09-01

Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven labelers. We also compared the performance of the passive and active learning models when using the consensus label. The AL methods: produced, for the models induced from each labeler, smoother Intra-labeler learning curves during the training phase, compared to the models produced when using the passive learning method. The mean standard deviation of the learning curves of the three AL methods over all labelers (mean: 0.0379; range: [0.0182 to 0.0496]), was significantly lower (p=0.049) than the Intra-labeler standard deviation when using the passive learning method (mean: 0.0484; range: [0.0275-0.0724). Using the AL methods resulted in a lower mean Inter-labeler AUC standard deviation among the AUC values of the labelers' different models during the training phase, compared to the variance of the induced models' AUC values when using passive learning. The Inter-labeler AUC standard deviation, using the passive learning method (0.039), was almost twice as high as the Inter-labeler standard deviation using our two new AL methods (0.02 and 0.019, respectively). The SVM-Margin AL method resulted in an Inter-labeler standard deviation (0.029) that was higher by almost 50% than that of our two AL methods The difference in the inter-labeler standard deviation between the passive learning method and the SVM-Margin learning method was significant (p=0.042). The difference between the SVM-Margin and Exploitation method was insignificant (p=0.29), as was the difference between the Combination_XA and Exploitation methods (p=0.67). Finally, using the consensus label led to a learning curve that had a higher mean intra-labeler variance, but resulted eventually in an AUC that was at least as high as the AUC achieved using the gold standard label and that was always higher than the expected mean AUC of a randomly selected labeler, regardless of the choice of learning method (including a passive learning method). Using a paired t-test, the difference between the intra-labeler AUC standard deviation when using the consensus label, versus that value when using the other two labeling strategies, was significant only when using the passive learning method (p=0.014), but not when using any of the three AL methods. The use of AL methods, (a) reduces intra-labeler variability in the performance of the induced models during the training phase, and thus reduces the risk of halting the process at a local minimum that is significantly different in performance from the rest of the learned models; and (b) reduces Inter-labeler performance variance, and thus reduces the dependence on the use of a particular labeler. In addition, the use of a consensus label, agreed upon by a rather uneven group of labelers, might be at least as good as using the gold standard labeler, who might not be available, and certainly better than randomly selecting one of the group's individual labelers. Finally, using the AL methods: when provided by the consensus label reduced the intra-labeler AUC variance during the learning phase, compared to using passive learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Practically perfect: learning by doing at AVS congress.

PubMed

2017-02-18

It has been some time since Cambridge vet school last hosted the annual AVS congress, which meant that this year's congress committee faced a steep learning curve. However, as Gill Harris reports, it rose to the occasion. British Veterinary Association.

Reduplicated Words Are Easier to Learn

ERIC Educational Resources Information Center

Ota, Mitsuhiko; Skarabela, Barbora

2016-01-01

Infants' disposition to learn repetitions in the input structure has been demonstrated in pattern generalization (e.g., learning the pattern ABB from the token "ledidi"). This study tested whether a repetition advantage can also be found in lexical learning (i.e., learning the word "lele" vs. "ledi"). Twenty-four…

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods

DTIC Science & Technology

2017-05-22

Influence of postnatal glucocorticoids on hippocampal-dependent learning varies with elevation patterns and administration methods 5b. GRANT NUMBER...of these effects varies with the elevation patterns (level, duration, temporal fluctuation) achieved by different administration methods . In general...learning varies with elevation patterns and administration methods Dragana I. Claflin a, Kevin D. Schmidt a, Zachary D. Vallandingham b, Michal

Patterns in clinical students' self-regulated learning behavior: a Q-methodology study.

PubMed

Berkhout, Joris J; Teunissen, Pim W; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P M; Jaarsma, Debbie A D C

2017-03-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in undergraduate students' self-regulated learning behavior in the clinical environment, to improve tailored supervision, using Q-methodology. Q-methodology uses features of both qualitative and quantitative methods for the systematic investigation of subjective issues by having participants sort statements along a continuum to represent their opinion. We enrolled 74 students between December 2014 and April 2015 and had them characterize their learning behavior by sorting 52 statements about self-regulated learning behavior and explaining their response. The statements used for the sorting were extracted from a previous study. The data was analyzed using by-person factor analysis to identify clusters of individuals with similar sorts of the statements. The resulting factors and qualitative data were used to interpret and describe the patterns that emerged. Five resulting patterns were identified in students' self-regulated learning behavior in the clinical environment, which we labelled: Engaged, Critically opportunistic, Uncertain, Restrained and Effortful. The five patterns varied mostly regarding goals, metacognition, communication, effort, and dependence on external regulation for learning. These discrete patterns in students' self-regulated learning behavior in the clinical environment are part of a complex interaction between student and learning context. The results suggest that developing self-regulated learning behavior might best be supported regarding individual students' needs.

Research Issues in Evaluating Learning Pattern Development in Higher Education

ERIC Educational Resources Information Center

Richardson, John T. E.

2013-01-01

This article concludes the special issue of "Studies in Educational Evaluation" concerned with "Evaluating learning pattern development in higher education" by discussing research issues that have emerged from the previous contributions. The article considers in turn: stability versus variability in learning patterns; old versus new analytic…

Establishing the minimal number of virtual reality simulator training sessions necessary to develop basic laparoscopic skills competence: evaluation of the learning curve.

PubMed

Duarte, Ricardo Jordão; Cury, José; Oliveira, Luis Carlos Neves; Srougi, Miguel

2013-01-01

Medical literature is scarce on information to define a basic skills training program for laparoscopic surgery (peg and transferring, cutting, clipping). The aim of this study was to determine the minimal number of simulator sessions of basic laparoscopic tasks necessary to elaborate an optimal virtual reality training curriculum. Eleven medical students with no previous laparoscopic experience were spontaneously enrolled. They were submitted to simulator training sessions starting at level 1 (Immersion Lap VR, San Jose, CA), including sequentially camera handling, peg and transfer, clipping and cutting. Each student trained twice a week until 10 sessions were completed. The score indexes were registered and analyzed. The total of errors of the evaluation sequences (camera, peg and transfer, clipping and cutting) were computed and thereafter, they were correlated to the total of items evaluated in each step, resulting in a success percent ratio for each student for each set of each completed session. Thereafter, we computed the cumulative success rate in 10 sessions, obtaining an analysis of the learning process. By non-linear regression the learning curve was analyzed. By the non-linear regression method the learning curve was analyzed and a r2 = 0.73 (p < 0.001) was obtained, being necessary 4.26 (∼five sessions) to reach the plateau of 80% of the estimated acquired knowledge, being that 100% of the students have reached this level of skills. From the fifth session till the 10th, the gain of knowledge was not significant, although some students reached 96% of the expected improvement. This study revealed that after five simulator training sequential sessions the students' learning curve reaches a plateau. The forward sessions in the same difficult level do not promote any improvement in laparoscopic basic surgical skills, and the students should be introduced to a more difficult training tasks level.

Learning curves and impact of previous operative experience on performance on a virtual reality simulator to test laparoscopic surgical skills.

PubMed

Grantcharov, Teodor P; Bardram, Linda; Funch-Jensen, Peter; Rosenberg, Jacob

2003-02-01

The study was carried out to analyze the learning rate for laparoscopic skills on a virtual reality training system and to establish whether the simulator was able to differentiate between surgeons with different laparoscopic experience. Forty-one surgeons were divided into three groups according to their experience in laparoscopic surgery: masters (group 1, performed more than 100 cholecystectomies), intermediates (group 2, between 15 and 80 cholecystectomies), and beginners (group 3, fewer than 10 cholecystectomies) were included in the study. The participants were tested on the Minimally Invasive Surgical Trainer-Virtual Reality (MIST-VR) 10 consecutive times within a 1-month period. Assessment of laparoscopic skills included time, errors, and economy of hand movement, measured by the simulator. The learning curves regarding time reached plateau after the second repetition for group 1, the fifth repetition for group 2, and the seventh repetition for group 3 (Friedman's tests P <0.05). Experienced surgeons did not improve their error or economy of movement scores (Friedman's tests, P >0.2) indicating the absence of a learning curve for these parameters. Group 2 error scores reached plateau after the first repetition, and group 3 after the fifth repetition. Group 2 improved their economy of movement score up to the third repetition and group 3 up to the sixth repetition (Friedman's tests, P <0.05). Experienced surgeons (group 1) demonstrated best performance parameters, followed by group 2 and group 3 (Mann-Whitney test P <0.05). Different learning curves existed for surgeons with different laparoscopic background. The familiarization rate on the simulator was proportional to the operative experience of the surgeons. Experienced surgeons demonstrated best laparoscopic performance on the simulator, followed by those with intermediate experience and the beginners. These differences indicate that the scoring system of MIST-VR is sensitive and specific to measuring skills relevant for laparoscopic surgery.

Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

PubMed

Chen, Lujie; Dubrawski, Artur; Wang, Donghan; Fiterau, Madalina; Guillame-Bert, Mathieu; Bose, Eliezer; Kaynar, Ata M; Wallace, David J; Guttendorf, Jane; Clermont, Gilles; Pinsky, Michael R; Hravnak, Marilyn

2016-07-01

The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability. Observational cohort study. Twenty-four-bed trauma step-down unit. Two thousand one hundred fifty-three patients. Noninvasive vital sign monitoring data (heart rate, respiratory rate, peripheral oximetry) recorded on all admissions at 1/20 Hz, and noninvasive blood pressure less frequently, and partitioned data into training/validation (294 admissions; 22,980 monitoring hours) and test sets (2,057 admissions; 156,177 monitoring hours). Alerts were vital sign deviations beyond stability thresholds. A four-member expert committee annotated a subset of alerts (576 in training/validation set, 397 in test set) as real or artifact selected by active learning, upon which we trained machine-learning algorithms. The best model was evaluated on test set alerts to enact online alert classification over time. The Random Forest model discriminated between real and artifact as the alerts evolved online in the test set with area under the curve performance of 0.79 (95% CI, 0.67-0.93) for peripheral oximetry at the instant the vital sign first crossed threshold and increased to 0.87 (95% CI, 0.71-0.95) at 3 minutes into the alerting period. Blood pressure area under the curve started at 0.77 (95% CI, 0.64-0.95) and increased to 0.87 (95% CI, 0.71-0.98), whereas respiratory rate area under the curve started at 0.85 (95% CI, 0.77-0.95) and increased to 0.97 (95% CI, 0.94-1.00). Heart rate alerts were too few for model development. Machine-learning models can discern clinically relevant peripheral oximetry, blood pressure, and respiratory rate alerts from artifacts in an online monitoring dataset (area under the curve > 0.87).

[Evaluation of the learning curve of residents in localizing a phantom target with ultrasonography].

PubMed

Dessieux, T; Estebe, J-P; Bloc, S; Mercadal, L; Ecoffey, C

2008-10-01

Few information are available regarding the learning curve in ultrasonography and even less for ultrasound-guided regional anesthesia. This study aimed to evaluate in a training program the learning curve on a phantom of 12 residents novice in ultrasonography. Twelve trainees inexperienced in ultrasonography were given introductory training consisting of didactic formation on the various components of the portable ultrasound machine (i.e. on/off button, gain, depth, resolution, and image storage). Then, students performed three trials, in two sets of increased difficulty, at executing these predefined tasks: adjustments of the machine, then localization of a small plastic piece introduced into roasting pork (3 cm below the surface). At the end of the evaluation, the residents were asked to insert a 22 G needle into an exact predetermined target (i.e. point of fascia intersection). The progression of the needle was continuously controlled by ultrasound visualization using injection of a small volume of water (needle perpendicular to the longitudinal plane of the ultrasound beam). Two groups of two different examiners evaluated for each three trials the skill of the residents (quality, time to perform the machine adjustments, to localize the plastic target, and to hydrolocalize, and volume used for hydrolocalization). After each trial, residents evaluated their performance using a difficulty scale (0: easy to 10: difficult). All residents performed the adjustments from the last trial of each set, with a learning curve observed in terms of duration. Localization of the plastic piece was achieved by all residents at the 6th trial, with a shorter duration of localization. Hydrolocalization was achieved after the 4th trial by all subjects. Difficulty scale was correlated to the number of trials. All these results were independent of the experience of residents in regional anesthesia. Four trials were necessary to adjust correctly the machine, to localize a target, and to complete hydrolocalization. Ultrasonography in regional anesthesia seems to be a fast-learning technique, using this kind of practical training.

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning

PubMed Central

Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-01-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. Here we show that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) are dynamically reformatted in the network at the timescale of a single breath, giving rise to separated patterns of activity in ensemble of output neurons (mitral/tufted cells; M/T). Strikingly, the extent of pattern separation in M/T assemblies predicts behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimuli distinction, a process that is sculpted by synaptic inhibition. PMID:26301325

Neuronal pattern separation in the olfactory bulb improves odor discrimination learning.

PubMed

Gschwend, Olivier; Abraham, Nixon M; Lagier, Samuel; Begnaud, Frédéric; Rodriguez, Ivan; Carleton, Alan

2015-10-01

Neuronal pattern separation is thought to enable the brain to disambiguate sensory stimuli with overlapping features, thereby extracting valuable information. In the olfactory system, it remains unknown whether pattern separation acts as a driving force for sensory discrimination and the learning thereof. We found that overlapping odor-evoked input patterns to the mouse olfactory bulb (OB) were dynamically reformatted in the network on the timescale of a single breath, giving rise to separated patterns of activity in an ensemble of output neurons, mitral/tufted (M/T) cells. Notably, the extent of pattern separation in M/T assemblies predicted behavioral discrimination performance during the learning phase. Furthermore, exciting or inhibiting GABAergic OB interneurons, using optogenetics or pharmacogenetics, altered pattern separation and thereby odor discrimination learning in a bidirectional way. In conclusion, we propose that the OB network can act as a pattern separator facilitating olfactory stimulus distinction, a process that is sculpted by synaptic inhibition.

Proactive transfer of learning depends on the evolution of prior learned task in memory.

PubMed

Tallet, Jessica; Kostrubiec, Viviane; Zanone, Pier-Giorgio

2010-06-01

The aim of the present study was to investigate the processes underlying the proactive interference effect using bimanual coordination. Our rationale was that interference would only occur when the prior learned A coordination pattern enters in competition with the required subsequent B pattern. We hypothesized that competition would arise only if the A pattern persists in memory before introducing the B pattern. In the experimental group, both A and B patterns were practiced and recalled, whereas in the control group only the B pattern was practiced and recalled. In Experiment 1, which involved initially bistable participants, the persistence of the A pattern led to interference, while, surprisingly, the A pattern forgetting entailed facilitation. In Experiment 2, which involved initially tristable participants, no such transfer effect was found. The apparently contradictory results can be interpreted coherently in the light of dynamical principles of learning. (c) 2010 Elsevier B.V. All rights reserved.

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

ERIC Educational Resources Information Center

Hung, Jui-Long; Crooks, Steven M.

2009-01-01

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and…

Bioconvective patterns, synchrony, and survival. [in light-limited growth model of motile algae culture

NASA Technical Reports Server (NTRS)

Noever, David A.

1990-01-01

With and without bioconvective pattern formation, a theoretical model predicts growth in light-limited cultures of motile algae. At the critical density for pattern formation, the resulting doubly exponential population curves show an inflection. Such growth corresponds quantitatively to experiments in mechanically unstirred cultures. This attaches survival value to synchronized pattern formation.

Learning Curves for Ultrasound Assessment of Lumbar Puncture Insertion Sites: When is Competency Established?

PubMed

Rankin, Jessica H; Elkhunovich, Marsha A; Rangarajan, Vijayeta; Chilstrom, Mikaela; Mailhot, Tom

2016-07-01

Ultrasound (US) can be used to improve lumbar puncture (LP) success. How to achieve competency in LP US has not been defined. Cumulative sum statistics (CUSUM) characterized competency acquisition in other skills. Identify the learning curve for 80% success rate in LP US insertion site (IS) identification among pediatric emergency medicine fellows. This prospective study took place in a single pediatric emergency department. Fellows with limited ultrasound experience received didactics, training, and three proctored examinations. Skills were evaluated in three 2-h sessions: using US, subjects identified LP ISs on a convenience sample of patients ages 0-20 years old. Subjects' IS markings were compared to markings by an expert, an emergency US fellowship-trained attending. Successful IS identification was defined as markings within 2 mm or 5 mm of the expert mark in infants and older children, respectively. A second expert marked 17 cases for interrater agreement. CUSUM was used to analyze individual learning curves. Five fellows evaluated 72 patients (mean age 11.4 years [SD = 4, range 3-20], mean body mass index 20.5 [SD = 4.4, range 13.1-37.7]) over a 3-month period. Mean number of attempts per fellow was 14.4 ± 3.1 (R 11-19); mean time to landmark identification was 72 ± 46 s (R 27-240). The two experts demonstrated 100% observed agreement. Aggregate success rate for all fellows was 75% (54/72). Four fellows showed learning curves that trended toward, but did not achieve, the acceptable success rate of 80%. Nineteen attempts are insufficient among fellows to achieve competency in US-guided LP IS identification. Copyright © 2016 Elsevier Inc. All rights reserved.

[HoLEP learning curve: Toward a standardised formation and a team strategy].

PubMed

Baron, M; Nouhaud, F-X; Delcourt, C; Grise, P; Pfister, C; Cornu, J-N; Sibert, L

2016-09-01

Holmium laser enucleation of prostate (HoLEP) is renowned for the difficulty of its learning curve. Our aim was to evaluate the interest of a three-step tutorial in the HoLEP learning curve, in a university center. It is a retrospective, monocentric study of the 82 first procedures done consecutively by the same operator with a proctoring in early experience and after 40 procedures. For all patients were noted: enucleation efficiency (g/min), morcellation efficiency (g/min), percentage of enucleated tissue (enucleated tissue/adenome weigth evaluated by ultrasonography. g/g), perioperative morbidity (Clavien), length of hospital stay, length of urinary drainage, functional outcomes at short and middle term (Qmax, post-void residual volume [PVR], QOL scores and IPSS at 3 and 6months). Enucleation and morcellation efficiency were significantly higher after the second proctoring (0.87 vs 0.44g/min; P<0.0001 and 4.2 vs 3.37g/min, P=0.038, respectively) so as the prostatic volume (43.5 vs 68.1mL, P=0.0001). Percentage of enucleated tissue was higher in the second group, however, the difference was not significant (69.5% vs 80.4%, P=0.03). Per- and postoperative complications, hospital length of stay, urinary drainage length and functional results at 3 and 6months were not significantly different. The learning curve did not interfere with functional results. The second proctoring was essential to us in order to grasp the technique. These data underlined the necessity of a pedagogic reflexion in order to built a standardized formation technique to the HoLEP. 4. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Analysis of the learning curve for pre-cut corneal specimens in preparation for lamellar transplantation: a prospective, single-centre, consecutive case series prepared at the Lions New South Wales Eye Bank.

PubMed

Martin, Aifric Isabel; Devasahayam, Rajnesh; Hodge, Christopher; Cooper, Simon; Sutton, Gerard L

2017-09-01

This study is the first paper to establish a learning curve by a single technician. Preparation of pre-cut corneal endothelial grafts commenced at Lions New South Wales Eye Bank in December 2014. The primary objective of this study was to review the safety and reliability of the preparation method during the first year of production. This is a hospital-based, prospective case series. There were 234 consecutive donor corneal lenticules. Donor lenticules were prepared by a single operator using a linear cutting microkeratome. Immediately prior to cutting, central corneal thickness values were recorded. Measurements of the corneal bed were taken immediately following lenticule preparation. Outcomes were separated by blade sizes, and intended thickness was compared to actual thickness for each setting. Early specimens were compared to later ones to assess for a learning curve within the technique. The main parameter measured is the mean difference from intended lamellar cut thickness. The mean final cut thickness was 122.36 ± 20.35 μm, and the mean difference from intended cut was 30.17 ± 37.45 μm. No significant difference was found between results achieved with early specimens versus those achieved with later specimens (P = 0.425). Thin, reproducible endothelial grafts can routinely be produced by trained technicians at their respective eye banks without significant concerns for an extended learning curve. This service can reduce perioperative surgical complexity, required surgical paraphernalia and theatre times. The consistent preparation of single-pass, ultrathin pre-cut corneas may have additional advantages for surgeons seeking to introduce lamellar techniques. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

Value of the cumulative sum test for the assessment of a learning curve: Application to the introduction of patient-specific instrumentation for total knee arthroplasty in an academic department.

PubMed

De Gori, Marco; Adamczewski, Benjamin; Jenny, Jean-Yves

2017-06-01

The purpose of the study was to use the cumulative summation (CUSUM) test to assess the learning curve during the introduction of a new surgical technique (patient-specific instrumentation) in total knee arthroplasty (TKA) in an academic department. The first 50TKAs operated on at an academic department using patient-specific templates (PSTs) were scheduled to enter the study. All patients had a preoperative computed tomography scan evaluation to plan bone resections. The PSTs were positioned intraoperatively according to the best-fit technique and their three-dimensional orientation was recorded by a navigation system. The position of the femur and tibia PST was compared to the planned position for four items for each component: coronal and sagittal orientation, medial and lateral height of resection. Items were summarized to obtain knee, femur and tibia PST scores, respectively. These scores were plotted according to chronological order and included in a CUSUM analysis. The tested hypothesis was that the PST process for TKA was immediately under control after its introduction. CUSUM test showed that positioning of the PST significantly differed from the target throughout the study. There was a significant difference between all scores and the maximal score. No case obtained the maximal score of eight points. The study was interrupted after 20 cases because of this negative evaluation. The CUSUM test is effective in monitoring the learning curve when introducing a new surgical procedure. Introducing PST for TKA in an academic department may be associated with a long-lasting learning curve. The study was registered on the clinical.gov website (Identifier NCT02429245). Copyright © 2017 Elsevier B.V. All rights reserved.

The learning curve to achieve satisfactory completion rates in upper GI endoscopy: an analysis of a national training database.

PubMed

Ward, S T; Hancox, A; Mohammed, M A; Ismail, T; Griffiths, E A; Valori, R; Dunckley, P

2017-06-01

The aim of this study was to determine the number of OGDs (oesophago-gastro-duodenoscopies) trainees need to perform to acquire competency in terms of successful unassisted completion to the second part of the duodenum 95% of the time. OGD data were retrieved from the trainee e-portfolio developed by the Joint Advisory Group on GI Endoscopy (JAG) in the UK. All trainees were included unless they were known to have a baseline experience of >20 procedures or had submitted data for <20 procedures. The primary outcome measure was OGD completion, defined as passage of the endoscope to the second part of the duodenum without physical assistance. The number of OGDs required to achieve a 95% completion rate was calculated by the moving average method and learning curve cumulative summation (LC-Cusum) analysis. To determine which factors were independently associated with OGD completion, a mixed effects logistic regression model was constructed with OGD completion as the outcome variable. Data were analysed for 1255 trainees over 288 centres, representing 243 555 OGDs. By moving average method, trainees attained a 95% completion rate at 187 procedures. By LC-Cusum analysis, after 200 procedures, >90% trainees had attained a 95% completion rate. Total number of OGDs performed, trainee age and experience in lower GI endoscopy were factors independently associated with OGD completion. There are limited published data on the OGD learning curve. This is the largest study to date analysing the learning curve for competency acquisition. The JAG competency requirement for 200 procedures appears appropriate. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Three-Hand Endoscopic Endonasal Transsphenoidal Surgery: Experience With an Anatomy-Preserving Mononostril Approach Technique.

PubMed

Eseonu, Chikezie I; ReFaey, Karim; Pamias-Portalatin, Eva; Asensio, Javier; Garcia, Oscar; Boahene, Kofi D; Quiñones-Hinojosa, Alfredo

2018-02-01

Variations on the endoscopic transsphenoidal approach present unique surgical techniques that have unique effects on surgical outcomes, extent of resection (EOR), and anatomical complications. To analyze the learning curve and perioperative outcomes of the 3-hand endoscopic endonasal mononostril transsphenoidal technique. Prospective case series and retrospective data analysis of patients who were treated with the 3-hand transsphenoidal technique between January 2007 and May 2015 by a single neurosurgeon. Patient characteristics, preoperative presentation, tumor characteristics, operative times, learning curve, and postoperative outcomes were analyzed. Volumetric EOR was evaluated, and a logistic regression analysis was used to assess predictors of EOR. Two hundred seventy-five patients underwent an endoscopic transsphenoidal surgery using the 3-hand technique. One hundred eighteen patients in the early group had surgery between 2007 and 2010, while 157 patients in the late group had surgery between 2011 and 2015. Operative time was significantly shorter in the late group (161.6 min) compared to the early group (211.3 min, P = .001). Both cohorts had similar EOR (early group 84.6% vs late group 85.5%, P = .846) and postoperative outcomes. The learning curve showed that it took 54 cases to achieve operative proficiency with the 3-handed technique. Multivariate modeling suggested that prior resections and preoperative tumor size are important predictors for EOR. We describe a 3-hand, mononostril endoscopic transsphenoidal technique performed by a single neurosurgeon that has minimal anatomic distortion and postoperative complications. During the learning curve of this technique, operative time can significantly decrease, while EOR, postoperative outcomes, and complications are not jeopardized. Copyright © 2017 by the Congress of Neurological Surgeons

Learning Curve Analysis and Surgical Outcomes of Single-port Laparoscopic Myomectomy.

PubMed

Lee, Hee Jun; Kim, Ju Yeong; Kim, Seul Ki; Lee, Jung Ryeol; Suh, Chang Suk; Kim, Seok Hyun

2015-01-01

To identify learning curves for single-port laparoscopic myomectomy (SPLM) and evaluate surgical outcomes according to the sequence of operation. A retrospective study. A university-based hospital (Canadian Task Force classification II-2). The medical records from 205 patients who had undergone SPLM from October 2009 to May 2013 were reviewed. Because the myomectomy time was significantly affected by the size and number of myomas removed by SPLM, cases in which 2 or more of the myomas removed were >7 cm in diameter were excluded. Furthermore, cases involving additional operations performed simultaneously (e.g., ovarian or hysteroscopic surgery) were also excluded. A total of 161 cases of SPLM were included. None. We assessed the SPLM learning curve via a graph based on operation time versus sequence of cases. Patients were chronologically arranged according to their surgery dates and were then placed into 1 of 4 groups according to their operation sequence. SPLM was completed successfully in 160 of 161 cases (99.4%). One case was converted to multiport surgery. Basal characteristics of the patients between the 4 groups did not differ. The median operation times for the 4 groups were 112.0, 92.8, 83.7, and 90.0 minutes, respectively. Operation time decreased significantly in the second, third, and fourth groups compared with that in the first group (p < .001). Proficiency, which is the point at which the slope of the learning curve became less steep, was evident after about 45 operations. Results from the current study suggested that proficiency for SPLM was achieved after about 45 operations. Additionally, operation time decreased with experience without an increase in complication rate. Copyright © 2015 AAGL. Published by Elsevier Inc. All rights reserved.

The humpbacked species richness-curve: A contingent rule for community ecology

USGS Publications Warehouse

Graham, John H.; Duda, Jeffrey J.

2011-01-01

Functional relationships involving species richness may be unimodal, monotonically increasing, monotonically decreasing, bimodal, multimodal, U-shaped, or with no discernable pattern. The unimodal relationships are the most interesting because they suggest dynamic, nonequilibrium community processes. For that reason, they are also contentious. In this paper, we provide a wide-ranging review of the literature on unimodal (humpbacked) species richness-relationships. Though not as widespread as previously thought, unimodal patterns of species richness are often associated with disturbance, predation and herbivory, productivity, spatial heterogeneity, environmental gradients, time, and latitude. These unimodal patterns are contingent on organism and environment; we examine unimodal species richness-curves involving plants, invertebrates, vertebrates, plankton, and microbes in marine, lacustrine, and terrestrial habitats. A goal of future research is to understand the contingent patterns and the complex, interacting processes that generate them.

Exhaustive search system and method using space-filling curves

DOEpatents

Spires, Shannon V.

2003-10-21

A search system and method for one agent or for multiple agents using a space-filling curve provides a way to control one or more agents to cover an area of any space of any dimensionality using an exhaustive search pattern. An example of the space-filling curve is a Hilbert curve. The search area can be a physical geography, a cyberspace search area, or an area searchable by computing resources. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace.

Image analysis of speckle patterns as a probe of melting transitions in laser-heated diamond anvil cell experiments.

PubMed

Salem, Ran; Matityahu, Shlomi; Melchior, Aviva; Nikolaevsky, Mark; Noked, Ori; Sterer, Eran

2015-09-01

The precision of melting curve measurements using laser-heated diamond anvil cell (LHDAC) is largely limited by the correct and reliable determination of the onset of melting. We present a novel image analysis of speckle interference patterns in the LHDAC as a way to define quantitative measures which enable an objective determination of the melting transition. Combined with our low-temperature customized IR pyrometer, designed for measurements down to 500 K, our setup allows studying the melting curve of materials with low melting temperatures, with relatively high precision. As an application, the melting curve of Te was measured up to 35 GPa. The results are found to be in good agreement with previous data obtained at pressures up to 10 GPa.

Learning curve for peroral endoscopic myotomy

PubMed Central

El Zein, Mohamad; Kumbhari, Vivek; Ngamruengphong, Saowanee; Carson, Kathryn A.; Stein, Ellen; Tieu, Alan; Chaveze, Yamile; Ismail, Amr; Dhalla, Sameer; Clarke, John; Kalloo, Anthony; Canto, Marcia Irene; Khashab, Mouen A.

2016-01-01

Background and study aims: Although peroral endoscopic myotomy (POEM) is being performed more frequently, the learning curve for gastroenterologists performing the procedure has not been well studied. The aims of this study were to define the learning curve for POEM and determine which preoperative and intraoperative factors predict the time that will be taken to complete the procedure and its different steps. Patients and methods: Consecutive patients who underwent POEM performed by a single expert gastroenterologist for the treatment of achalasia or spastic esophageal disorders were included. The POEM procedure was divided into four steps: mucosal entry, submucosal tunneling, myotomy, and closure. Nonlinear regression was used to determine the POEM learning plateau and calculate the learning rate. Results: A total of 60 consecutive patients underwent POEM in an endoscopy suite. The median length of procedure (LOP) was 88 minutes (range 36 – 210), and the mean (± standard deviation [SD]) LOP per centimeter of myotomy was 9 ± 5 minutes. The total operative time decreased significantly as experience increased (P < 0.001), with a “learning plateau” at 102 minutes and a “learning rate” of 13 cases. The mucosal entry, tunneling, and closure times decreased significantly with experience (P < 0.001). The myotomy time showed no significant decrease with experience (P = 0.35). When the mean (± SD) total procedure times for the learning phase and the corresponding comparator groups were compared, a statistically significant difference was observed between procedures 11 – 15 and procedures 16 – 20 (15.5 ± 2.4 min/cm and 10.1 ± 2.7 min/cm, P = 0.01) but not thereafter. A higher case number was significantly associated with a decreased LOP (P < 0.001). Conclusion: In this single-center retrospective study, the minimum threshold number of cases required for an expert interventional endoscopist performing POEM to reach a plateau approached 13. PMID:27227118

Moore's curve structuring of ferromagnetic composite PE-NiFe absorbers

NASA Astrophysics Data System (ADS)

Fernez, N.; Arbaoui, Y.; Maalouf, A.; Chevalier, A.; Agaciak, P.; Burgnies, L.; Queffelec, P.; Laur, V.; Lheurette, É.

2018-02-01

A ferromagnetic material involving nickel-iron particles embedded in a polyethylene matrix is synthesized and electrically characterized between 1 and 12 GHz. These measurements show the combination of electric and magnetic activity along with significant loss terms. We take benefit of these properties for the design of broadband electromagnetic absorbers. To this aim, we use a fractal structuring based on Moore curves. The advantage of etching patterns over metallic ones is clearly evidenced, and several pattern absorbers identified by their Moore's order iteration are designed and analyzed under oblique incidence.

The role of consolidation in learning context-dependent phonotactic patterns in speech and digital sequence production.

PubMed

Anderson, Nathaniel D; Dell, Gary S

2018-04-03

Speakers implicitly learn novel phonotactic patterns by producing strings of syllables. The learning is revealed in their speech errors. First-order patterns, such as "/f/ must be a syllable onset," can be distinguished from contingent, or second-order, patterns, such as "/f/ must be an onset if the vowel is /a/, but a coda if the vowel is /o/." A metaanalysis of 19 experiments clearly demonstrated that first-order patterns affect speech errors to a very great extent in a single experimental session, but second-order vowel-contingent patterns only affect errors on the second day of testing, suggesting the need for a consolidation period. Two experiments tested an analogue to these studies involving sequences of button pushes, with fingers as "consonants" and thumbs as "vowels." The button-push errors revealed two of the key speech-error findings: first-order patterns are learned quickly, but second-order thumb-contingent patterns are only strongly revealed in the errors on the second day of testing. The influence of computational complexity on the implicit learning of phonotactic patterns in speech production may be a general feature of sequence production.

Curved-line search algorithm for ab initio atomic structure relaxation

NASA Astrophysics Data System (ADS)

Chen, Zhanghui; Li, Jingbo; Li, Shushen; Wang, Lin-Wang

2017-09-01

Ab initio atomic relaxations often take large numbers of steps and long times to converge, especially when the initial atomic configurations are far from the local minimum or there are curved and narrow valleys in the multidimensional potentials. An atomic relaxation method based on on-the-flight force learning and a corresponding curved-line search algorithm is presented to accelerate this process. Results demonstrate the superior performance of this method for metal and magnetic clusters when compared with the conventional conjugate-gradient method.

Learning Cue Phrase Patterns from Radiology Reports Using a Genetic Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, Robert M; Beckerman, Barbara G; Potok, Thomas E

2009-01-01

Various computer-assisted technologies have been developed to assist radiologists in detecting cancer; however, the algorithms still lack high degrees of sensitivity and specificity, and must undergo machine learning against a training set with known pathologies in order to further refine the algorithms with higher validity of truth. This work describes an approach to learning cue phrase patterns in radiology reports that utilizes a genetic algorithm (GA) as the learning method. The approach described here successfully learned cue phrase patterns for two distinct classes of radiology reports. These patterns can then be used as a basis for automatically categorizing, clustering, ormore » retrieving relevant data for the user.« less

Comparing rainfall patterns between regions in Peninsular Malaysia via a functional data analysis technique

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Jemain, Abdul Aziz; Hamdan, Muhammad Fauzee; Wan Zin, Wan Zawiah

2011-12-01

SummaryNormally, rainfall data is collected on a daily, monthly or annual basis in the form of discrete observations. The aim of this study is to convert these rainfall values into a smooth curve or function which could be used to represent the continuous rainfall process at each region via a technique known as functional data analysis. Since rainfall data shows a periodic pattern in each region, the Fourier basis is introduced to capture these variations. Eleven basis functions with five harmonics are used to describe the unimodal rainfall pattern for stations in the East while five basis functions which represent two harmonics are needed to describe the rainfall pattern in the West. Based on the fitted smooth curve, the wet and dry periods as well as the maximum and minimum rainfall values could be determined. Different rainfall patterns are observed among the studied regions based on the smooth curve. Using the functional analysis of variance, the test results indicated that there exist significant differences in the functional means between each region. The largest differences in the functional means are found between the East and Northwest regions and these differences may probably be due to the effect of topography and, geographical location and are mostly influenced by the monsoons. Therefore, the same inputs or approaches might not be useful in modeling the hydrological process for different regions.

Do Online Learning Patterns Exhibit Regional and Demographic Differences?

ERIC Educational Resources Information Center

Hsieh, Tsui-Chuan; Yang, Chyan

2012-01-01

This paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are…

Patterns of Learning in a Sample of Adult Returners to Higher Education

ERIC Educational Resources Information Center

Anderson, Anthony; Johnston, Bill; McDonald, Alexandra

2014-01-01

This article presents empirical research exploring adult returner students' patterns of learning via qualitative analysis of a series of semi-structured interviews. Interviewees' comments shed light on the relation between patterns of learning on the one hand, and study skills, epistemological issues and attitudes to peer interaction on the other.…

Learning curve analysis of mitral valve repair using telemanipulative technology.

PubMed

Charland, Patrick J; Robbins, Tom; Rodriguez, Evilio; Nifong, Wiley L; Chitwood, Randolph W

2011-08-01

To determine if the time required to perform mitral valve repairs using telemanipulation technology decreases with experience and how that decrease is influenced by patient and procedure variables. A single-center retrospective review was conducted using perioperative and outcomes data collected contemporaneously on 458 mitral valve repair surgeries using telemanipulative technology. A regression model was constructed to assess learning with this technology and predict total robot time using multiple predictive variables. Statistical analysis was used to determine if models were significantly useful, to rule out correlation between predictor variables, and to identify terms that did not contribute to the prediction of total robot time. We found a statistically significant learning curve (P < .01). The institutional learning percentage∗ derived from total robot times† for the first 458 recorded cases of mitral valve repair using telemanipulative technology is 95% (R(2) = .40). More than one third of the variability in total robot time can be explained through our model using the following variables: type of repair (chordal procedures, ablations, and leaflet resections), band size, use of clips alone in band implantation, and the presence of a fellow at bedside (P < .01). Learning in mitral valve repair surgery using telemanipulative technology occurs at the East Carolina Heart Institute according to a logarithmic curve, with a learning percentage of 95%. From our regression output, we can make an approximate prediction of total robot time using an additive model. These metrics can be used by programs for benchmarking to manage the implementation of this new technology, as well as for capacity planning, scheduling, and capital budget analysis. Copyright © 2011 The American Association for Thoracic Surgery. All rights reserved.

Eliciting design patterns for e-learning systems

NASA Astrophysics Data System (ADS)

Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

2006-06-01

Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

Using a High-Fidelity Patient Simulator with First-Year Medical Students to Facilitate Learning of Cardiovascular Function Curves

ERIC Educational Resources Information Center

Harris, David M.; Ryan, Kathleen; Rabuck, Cynthia

2012-01-01

Students are relying on technology for learning more than ever, and educators need to adapt to facilitate student learning. High-fidelity patient simulators (HFPS) are usually reserved for the clinical years of medical education and are geared to improve clinical decision skills, teamwork, and patient safety. Finding ways to incorporate HFPS into…

Patterns in Elementary School Students' Strategic Actions in Varying Learning Situations

ERIC Educational Resources Information Center

Malmberg, Jonna; Järvenoja, Hanna; Järvelä, Sanna

2013-01-01

This study uses log file traces to examine differences between high-and low-achieving students' strategic actions in varying learning situations. In addition, this study illustrates, in detail, what strategic and self-regulated learning constitutes in practice. The study investigates the learning patterns that emerge in learning situations…

Intra-storm temporal patterns of rainfall in China using Huff curves

USDA-ARS?s Scientific Manuscript database

The intra-storm temporal distributions of precipitation are important to infiltration, runoff and erosion processes and models. A convenient and established method for characterizing precipitation hyetographs is with the use of Huff curves. In this study, 11,801 erosive rainfall events with one-mi...

How to Avoid a Learning Curve in Stapedotomy: A Standardized Surgical Technique.

PubMed

Kwok, Pingling; Gleich, Otto; Dalles, Katharina; Mayr, Elisabeth; Jacob, Peter; Strutz, Jürgen

2017-08-01

To evaluate, whether a learning curve for beginners in stapedotomy can be avoided by using a prosthesis with thermal memory-shape attachment in combination with a standardized laser-assisted surgical technique. Retrospective case review. Tertiary referral center. Fifty-eight ears were operated by three experienced surgeons and compared with a group of 12 cases operated by a beginner in stapedotomy. Stapedotomy. Difference of pure-tone audiometry thresholds measured before and after surgery. The average postoperative gain for air conduction in the frequencies below 2 kHz was 20 to 25 dB and decreased for the higher frequencies. Using the Mann-Whitney-U test for comparing mean gain between experienced and inexperienced surgeons showed no significant difference (p = 0.281 at 4 kHz and p > 0.7 for the other frequencies). A Spearman rank correlation of the postoperative gain for air- and bone-conduction thresholds was obtained at each test frequency for the first 12 patients consecutively treated with a thermal memory-shape attachment prosthesis by two experienced and one inexperienced surgeon. This analysis does not support the hypothesis of a "learning effect" that should be associated with an improved outcome for successively treated patients. It is possible to avoid a learning curve in stapes surgery by applying a thermal memory-shape prosthesis in a standardized laser-assisted surgical procedure.

37. PATTERNS HANGING FROM CEILING AND OFFICE WALL, NOTE CRAFTSMANSHIP ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

37. PATTERNS HANGING FROM CEILING AND OFFICE WALL, NOTE CRAFTSMANSHIP OF CURVE-LOOKING NORTHWEST. - W. A. Young & Sons Foundry & Machine Shop, On Water Street along Monongahela River, Rices Landing, Greene County, PA

Runoff potentiality of a watershed through SCS and functional data analysis technique.

PubMed

Adham, M I; Shirazi, S M; Othman, F; Rahman, S; Yusop, Z; Ismail, Z

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling.

Runoff Potentiality of a Watershed through SCS and Functional Data Analysis Technique

PubMed Central

Adham, M. I.; Shirazi, S. M.; Othman, F.; Rahman, S.; Yusop, Z.; Ismail, Z.

2014-01-01

Runoff potentiality of a watershed was assessed based on identifying curve number (CN), soil conservation service (SCS), and functional data analysis (FDA) techniques. Daily discrete rainfall data were collected from weather stations in the study area and analyzed through lowess method for smoothing curve. As runoff data represents a periodic pattern in each watershed, Fourier series was introduced to fit the smooth curve of eight watersheds. Seven terms of Fourier series were introduced for the watersheds 5 and 8, while 8 terms of Fourier series were used for the rest of the watersheds for the best fit of data. Bootstrapping smooth curve analysis reveals that watersheds 1, 2, 3, 6, 7, and 8 are with monthly mean runoffs of 29, 24, 22, 23, 26, and 27 mm, respectively, and these watersheds would likely contribute to surface runoff in the study area. The purpose of this study was to transform runoff data into a smooth curve for representing the surface runoff pattern and mean runoff of each watershed through statistical method. This study provides information of runoff potentiality of each watershed and also provides input data for hydrological modeling. PMID:25152911

Noise power spectrum of the fixed pattern noise in digital radiography detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Dong Sik, E-mail: dskim@hufs.ac.kr; Kim, Eun

Purpose: The fixed pattern noise in radiography image detectors is caused by various sources. Multiple readout circuits with gate drivers and charge amplifiers are used to efficiently acquire the pixel voltage signals. However, the multiple circuits are not identical and thus yield nonuniform system gains. Nonuniform sensitivities are also produced from local variations in the charge collection elements. Furthermore, in phosphor-based detectors, the optical scattering at the top surface of the columnar CsI growth, the grain boundaries, and the disorder structure causes spatial sensitivity variations. These nonuniform gains or sensitivities cause fixed pattern noise and degrade the detector performance, evenmore » though the noise problem can be partially alleviated by using gain correction techniques. Hence, in order to develop good detectors, comparative analysis of the energy spectrum of the fixed pattern noise is important. Methods: In order to observe the energy spectrum of the fixed pattern noise, a normalized noise power spectrum (NNPS) of the fixed pattern noise is considered in this paper. Since the fixed pattern noise is mainly caused by the nonuniform gains, we call the spectrum the gain NNPS. We first asymptotically observe the gain NNPS and then formulate two relationships to calculate the gain NNPS based on a nonuniform-gain model. Since the gain NNPS values are quite low compared to the usual NNPS, measuring such a low NNPS value is difficult. By using the average of the uniform exposure images, a robust measuring method for the gain NNPS is proposed in this paper. Results: By using the proposed measuring method, the gain NNPS curves of several prototypes of general radiography and mammography detectors were measured to analyze their fixed pattern noise properties. We notice that a direct detector, which is based on the a-Se photoconductor, showed lower gain NNPS than the indirect-detector case, which is based on the CsI scintillator. By comparing the gain NNPS curves of the indirect detectors, we could analyze the scintillator properties depending on the techniques for the scintillator surface processing. Conclusions: A robust measuring method for the NNPS of the fixed pattern noise of a radiography detector is proposed in this paper. The method can measure a stable gain NNPS curve, even though the fixed pattern noise level is quite low. From the measured gain NNPS curves, we can compare and analyze the detector properties in terms of producing the fixed pattern noise.« less

Novel Uses of Video to Accelerate the Surgical Learning Curve.

PubMed

Ibrahim, Andrew M; Varban, Oliver A; Dimick, Justin B

2016-04-01

Surgeons are under enormous pressure to continually improve and learn new surgical skills. Novel uses of surgical video in the preoperative, intraoperative, and postoperative setting are emerging to accelerate the learning curve of surgical skill and minimize harm to patients. In the preoperative setting, social media outlets provide a valuable platform for surgeons to collaborate and plan for difficult operative cases. Live streaming of video has allowed for intraoperative telementoring. Finally, postoperative use of video has provided structure for peer coaching to evaluate and improve surgical skill. Applying these approaches into practice is becoming easier as most of our surgical platforms (e.g., laparoscopic, and endoscopy) now have video recording technology built in and video editing software has become more user friendly. Future applications of video technology are being developed, including possible integration into accreditation and board certification.

Spontaneous wettability patterning via creasing instability

PubMed Central

Chen, Dayong; McKinley, Gareth H.; Cohen, Robert E.

2016-01-01

Surfaces with patterned wettability contrast are important in industrial applications such as heat transfer, water collection, and particle separation. Traditional methods of fabricating such surfaces rely on microfabrication technologies, which are only applicable to certain substrates and are difficult to scale up and implement on curved surfaces. By taking advantage of a mechanical instability on a polyurethane elastomer film, we show that wettability patterns on both flat and curved surfaces can be generated spontaneously via a simple dip coating process. Variations in dipping time, sample prestress, and chemical treatment enable independent control of domain size (from about 100 to 500 μm), morphology, and wettability contrast, respectively. We characterize the wettability contrast using local surface energy measurements via the sessile droplet technique and tensiometry. PMID:27382170

Advances in Laparoscopic Colorectal Surgery.

PubMed

Parker, James Michael; Feldmann, Timothy F; Cologne, Kyle G

2017-06-01

Laparoscopic colorectal surgery has now become widely adopted for the treatment of colorectal neoplasia, with steady increases in utilization over the past 15 years. Common minimally invasive techniques include multiport laparoscopy, single-incision laparoscopy, and hand-assisted laparoscopy, with the choice of technique depending on several patient and surgeon factors. Laparoscopic colorectal surgery involves a robust learning curve, and fellowship training often lays the foundation for a high-volume laparoscopic practice. This article provides a summary of the various techniques for laparoscopic colorectal surgery, including operative steps, the approach to difficult patients, and the learning curve for proficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated Decision Tree Classification of Corneal Shape

PubMed Central

Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

2011-01-01

Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification problems. PMID:16357645

Brain-robot interface driven plasticity: Distributed modulation of corticospinal excitability.

PubMed

Kraus, Dominic; Naros, Georgios; Bauer, Robert; Leão, Maria Teresa; Ziemann, Ulf; Gharabaghi, Alireza

2016-01-15

Brain-robot interfaces (BRI) are studied as novel interventions to facilitate functional restoration in patients with severe and persistent motor deficits following stroke. They bridge the impaired connection in the sensorimotor loop by providing brain-state dependent proprioceptive feedback with orthotic devices attached to the hand or arm of the patients. The underlying neurophysiology of this BRI neuromodulation is still largely unknown. We investigated changes of corticospinal excitability with transcranial magnetic stimulation in thirteen right-handed healthy subjects who performed 40min of kinesthetic motor imagery receiving proprioceptive feedback with a robotic orthosis attached to the left hand contingent to event-related desynchronization of the right sensorimotor cortex in the β-band (16-22Hz). Neural correlates of this BRI intervention were probed by acquiring the stimulus-response curve (SRC) of both motor evoked potential (MEP) peak-to-peak amplitudes and areas under the curve. In addition, a motor mapping was obtained. The specificity of the effects was studied by comparing two neighboring hand muscles, one BRI-trained and one control muscle. Robust changes of MEP amplitude but not MEP area occurred following the BRI intervention, but only in the BRI-trained muscle. The steep part of the SRC showed an MEP increase, while the plateau of the SRC showed an MEP decrease. MEP mapping revealed a distributed pattern with a decrease of excitability in the hand area of the primary motor cortex, which controlled the BRI, but an increase of excitability in the surrounding somatosensory and premotor cortex. In conclusion, the BRI intervention induced a complex pattern of modulated corticospinal excitability, which may boost subsequent motor learning during physiotherapy. Copyright © 2015 Elsevier Inc. All rights reserved.

Brief periods of NREM sleep do not promote early offline gains but subsequent on-task performance in motor skill learning.

PubMed

Maier, Jonathan G; Piosczyk, Hannah; Holz, Johannes; Landmann, Nina; Deschler, Christoph; Frase, Lukas; Kuhn, Marion; Klöppel, Stefan; Spiegelhalder, Kai; Sterr, Annette; Riemann, Dieter; Feige, Bernd; Voderholzer, Ulrich; Nissen, Christoph

2017-11-01

Sleep modulates motor learning, but its detailed impact on performance curves remains to be fully characterized. This study aimed to further determine the impact of brief daytime periods of NREM sleep on 'offline' (task discontinuation after initial training) and 'on-task' (performance within the test session) changes in motor skill performance (finger tapping task). In a mixed design (combined parallel group and repeated measures) sleep laboratory study (n=17 'active' wake vs. sleep, n=19 'passive' wake vs. sleep), performance curves were assessed prior to and after a 90min period containing either sleep, active or passive wakefulness. We observed a highly significant, but state- (that is, sleep/wake)-independent early offline gain and improved on-task performance after sleep in comparison to wakefulness. Exploratory curve fitting suggested that the observed sleep effect most likely emerged from an interaction of training-induced improvement and detrimental 'time-on-task' processes, such as fatigue. Our results indicate that brief periods of NREM sleep do not promote early offline gains but subsequent on-task performance in motor skill learning. Copyright © 2017 Elsevier Inc. All rights reserved.

A variation reduction allocation model for quality improvement to minimize investment and quality costs by considering suppliers’ learning curve

NASA Astrophysics Data System (ADS)

Rosyidi, C. N.; Jauhari, WA; Suhardi, B.; Hamada, K.

2016-02-01

Quality improvement must be performed in a company to maintain its product competitiveness in the market. The goal of such improvement is to increase the customer satisfaction and the profitability of the company. In current practice, a company needs several suppliers to provide the components in assembly process of a final product. Hence quality improvement of the final product must involve the suppliers. In this paper, an optimization model to allocate the variance reduction is developed. Variation reduction is an important term in quality improvement for both manufacturer and suppliers. To improve suppliers’ components quality, the manufacturer must invest an amount of their financial resources in learning process of the suppliers. The objective function of the model is to minimize the total cost consists of investment cost, and quality costs for both internal and external quality costs. The Learning curve will determine how the employee of the suppliers will respond to the learning processes in reducing the variance of the component.

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

PubMed

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

What is the learning curve for robotic-assisted pedicle screw placement in spine surgery?

PubMed

Hu, Xiaobang; Lieberman, Isador H

2014-06-01

Some early studies with robotic-assisted pedicle screw implantation have suggested these systems increase accuracy of screw placement. However, the relationship between the success rate of screw placement and the learning curve of this new technique has not been evaluated. We determined whether, as a function of surgeon experience, (1) the success rate of robotic-assisted pedicle screw placement improved, (2) the frequency of conversion from robotic to manual screw placement decreased, and (3) the frequency of malpositioned screws decreased. Between June 2010 and August 2012, the senior surgeon (IHL) performed 174 posterior spinal procedures using pedicle screws, 162 of which were attempted with robotic assistance. The use of the robotic system was aborted in 12 of the 162 procedures due to technical issues (registration failure, software crash, etc). The robotic system was successfully used in the remaining 150 procedures. These were the first procedures performed with the robot by the senior surgeon, and in this study, we divided the early learning curve into five groups: Group 1 (Patients 1-30), Group 2 (Patients 31-60), Group 3 (Patients 61-90), Group 4 (Patients 91-120), and Group 5 (Patients 121-150). One hundred twelve patients (75%) had spinal deformity and 80 patients (53%) had previous spine surgery. The accuracy of screw placement in the groups was assessed based on intraoperative biplanar fluoroscopy and postoperative radiographs. The results from these five groups were compared to determine the effect on the learning curve. The numbers of attempted pedicle screw placements were 359, 312, 349, 359, and 320 in Groups 1 to 5, respectively. The rates of successfully placed screws using robotic guidance were 82%, 93%, 91%, 95%, and 93% in Groups 1 to 5. The rates of screws converted to manual placement were 17%, 7%, 8%, 4%, and 7%. Of the robotically placed screws, the screw malposition rates were 0.8%, 0.3%, 1.4%, 0.8%, and 0%. The rate of successfully placed pedicle screws improved with increasing experience. The rate of the screws that were converted to manual placement decreased with increasing experience. The frequency of screw malposition was similar over the learning curve at 0% to 1.4%. Future studies will need to determine whether this finding is generalizable to others. Level III, therapeutic study. See the Instructions for Authors for a complete description of levels of evidence.

Grammatical pattern learning by human infants and cotton-top tamarin monkeys

PubMed Central

Saffran, Jenny; Hauser, Marc; Seibel, Rebecca; Kapfhamer, Joshua; Tsao, Fritz; Cushman, Fiery

2008-01-01

There is a surprising degree of overlapping structure evident across the languages of the world. One factor leading to cross-linguistic similarities may be constraints on human learning abilities. Linguistic structures that are easier for infants to learn should predominate in human languages. If correct, then (a) human infants should more readily acquire structures that are consistent with the form of natural language, whereas (b) non-human primates’ patterns of learning should be less tightly linked to the structure of human languages. Prior experiments have not directly compared laboratory-based learning of grammatical structures by human infants and non-human primates, especially under comparable testing conditions and with similar materials. Five experiments with 12-month-old human infants and adult cotton-top tamarin monkeys addressed these predictions, employing comparable methods (familiarization-discrimination) and materials. Infants rapidly acquired complex grammatical structures by using statistically predictive patterns, failing to learn structures that lacked such patterns. In contrast, the tamarins only exploited predictive patterns when learning relatively simple grammatical structures. Infant learning abilities may serve both to facilitate natural language acquisition and to impose constraints on the structure of human languages. PMID:18082676

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

Learning a New Selection Rule in Visual and Frontal Cortex.

PubMed

van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

2016-08-01

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

Spaghetti Sine Curves: Virtual Environments for Reasoning and Sense Making

ERIC Educational Resources Information Center

Özgün-Koca, S. Asli; Edwards, Michael Todd; Meagher, Michael

2013-01-01

In a recent collaboration with an area high school teacher, the authors were asked to develop an introductory sinusoidal curves lesson for a group of second-year algebra students. Because the topic was abstract and unfamiliar to these tenth graders, they looked for hands-on lessons to support their learning. One lesson that they found, which they…

Developing a Drawing Task to Differentiate Group Average Time Course vs. Dynamics in the Individual

ERIC Educational Resources Information Center

Blech, Christine; Gaschler, Robert

2017-01-01

Teaching and theorizing in psychology has long been torn between targeting general underlying principles by observing dynamics in the individual or focusing on average behavior. As dealing with group averages is common practice in psychology, it is important for students to understand how individual learning curves relate to group average curves.…

Movement Pattern and Parameter Learning in Children: Effects of Feedback Frequency

ERIC Educational Resources Information Center

Goh, Hui-Ting; Kantak, Shailesh S.; Sullivan, Katherine J.

2012-01-01

Reduced feedback during practice has been shown to be detrimental to movement accuracy in children but not in young adults. We hypothesized that the reduced accuracy is attributable to reduced movement parameter learning, but not pattern learning, in children. A rapid arm movement task that required the acquisition of a motor pattern scaled to…

Eye Gaze and Production Accuracy Predict English L2 Speakers' Morphosyntactic Learning

ERIC Educational Resources Information Center

McDonough, Kim; Trofimovich, Pavel; Dao, Phung; Dio, Alexandre

2017-01-01

This study investigated the relationship between second language (L2) speakers' success in learning a new morphosyntactic pattern and characteristics of one-on-one learning activities, including opportunities to comprehend and produce the target pattern, receive feedback from an interlocutor, and attend to the meaning of the pattern through self-…

Analysis of Laparoscopic Sleeve Gastrectomy Learning Curve and Its Influence on Procedure Safety and Perioperative Complications.

PubMed

Major, Piotr; Wysocki, Michał; Dworak, Jadwiga; Pędziwiatr, Michał; Pisarska, Magdalena; Wierdak, Mateusz; Zub-Pokrowiecka, Anna; Natkaniec, Michał; Małczak, Piotr; Nowakowski, Michał; Budzyński, Andrzej

2018-06-01

Laparoscopic sleeve gastrectomy (LSG) has become an attractive bariatric procedure with promising treatment effects yet amount of data regarding institutional learning process is limited. Retrospective study included patients submitted to LSG at academic teaching hospital. Patients were divided into groups every 100 consecutive patients. LSG introduction was structured along with Enhanced Recovery after Surgery (ERAS) treatment protocol. Primary endpoint was determining the LSG learning curve's stabilization point, using operative time, intraoperative difficulties, intraoperative adverse events (IAE), and number of stapler firings. Secondary endpoints: influence on perioperative complications and reoperations. Five hundred patients were included (330 females, median age of 40 (33-49) years). Operative time in G1-G2 differed significantly from G3-G5. Stabilization point was the 200th procedure using operative time. Intraoperative difficulties of G1 differed significantly from G2-G5, with stabilization after the 100th procedure. IAE and number of stapler firings could not be used as predictor. Based on perioperative morbidity, the learning curve was stabilized at the 100th procedure. The morbidity rates in the groups were G1, 13%; G2, 4%; G3, 5%; G4, 5%; and G5, 2%. The reoperation rate in G1 was 3%; G2, 2%; G3, 2%; G4, 1%; and G5, 0%. The institutional learning process stabilization point for LSG in a newly established bariatric center is between the 100th and 200th operation. Initially, the morbidity rate is high, which should concern surgeons who are willing to perform bariatric surgery.

Laparoscopic colorectal surgery in learning curve: Role of implementation of a standardized technique and recovery protocol. A cohort study

PubMed Central

Luglio, Gaetano; De Palma, Giovanni Domenico; Tarquini, Rachele; Giglio, Mariano Cesare; Sollazzo, Viviana; Esposito, Emanuela; Spadarella, Emanuela; Peltrini, Roberto; Liccardo, Filomena; Bucci, Luigi

2015-01-01

Background Despite the proven benefits, laparoscopic colorectal surgery is still under utilized among surgeons. A steep learning is one of the causes of its limited adoption. Aim of the study is to determine the feasibility and morbidity rate after laparoscopic colorectal surgery in a single institution, “learning curve” experience, implementing a well standardized operative technique and recovery protocol. Methods The first 50 patients treated laparoscopically were included. All the procedures were performed by a trainee surgeon, supervised by a consultant surgeon, according to the principle of complete mesocolic excision with central vascular ligation or TME. Patients underwent a fast track recovery programme. Recovery parameters, short-term outcomes, morbidity and mortality have been assessed. Results Type of resections: 20 left side resections, 8 right side resections, 14 low anterior resection/TME, 5 total colectomy and IRA, 3 total panproctocolectomy and pouch. Mean operative time: 227 min; mean number of lymph-nodes: 18.7. Conversion rate: 8%. Mean time to flatus: 1.3 days; Mean time to solid stool: 2.3 days. Mean length of hospital stay: 7.2 days. Overall morbidity: 24%; major morbidity (Dindo–Clavien III): 4%. No anastomotic leak, no mortality, no 30-days readmission. Conclusion Proper laparoscopic colorectal surgery is safe and leads to excellent results in terms of recovery and short term outcomes, even in a learning curve setting. Key factors for better outcomes and shortening the learning curve seem to be the adoption of a standardized technique and training model along with the strict supervision of an expert colorectal surgeon. PMID:25859386

Life form influences survivorship patterns for 109 herbaceous perennials from six semi-arid ecosystems

USDA-ARS?s Scientific Manuscript database

We compiled six long-term datasets from western North America to test for ecosystem-dependent demographic responses for forbs and grasses. Based on these data, we characterized 123 survivorship curves for 109 species. Three demographic parameters were extracted from these survivorship curves: surviv...

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

GEsture: an online hand-drawing tool for gene expression pattern search.

PubMed

Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning

2018-01-01

Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.

QUANTITATIVE STUDIES ON THE TOTAL PLASMIN AND THE TRYPSIN INHIBITOR OF HUMAN BLOOD SERUM

PubMed Central

Todd, Edgar W.

1949-01-01

The total plasmin and the trypsin inhibitor were titrated separately in samples of serum taken at weekly intervals from three different groups of scarlet fever patients: (a) those who did not develop any complications, (b) those who developed purulent complications, and (c) those who developed rheumatic fever. When these determinations were plotted, it was found that the resulting curves showed characteristic patterns for each of the diseases investigated. The uncomplicated cases had plasmin curves which were considerably higher on the charts than the inhibitor curves. The septic cases had plasmin and inhibitor curves which were closer together on the charts. The rheumatic cases had plasmin and inhibitor curves which were close together and which crossed at the time of rheumatic activity so that the inhibitor curve reached a higher level than the plasmin curve. PMID:18110885

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

PubMed Central

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Surface modeling method for aircraft engine blades by using speckle patterns based on the virtual stereo vision system

NASA Astrophysics Data System (ADS)

Yu, Zhijing; Ma, Kai; Wang, Zhijun; Wu, Jun; Wang, Tao; Zhuge, Jingchang

2018-03-01

A blade is one of the most important components of an aircraft engine. Due to its high manufacturing costs, it is indispensable to come up with methods for repairing damaged blades. In order to obtain a surface model of the blades, this paper proposes a modeling method by using speckle patterns based on the virtual stereo vision system. Firstly, blades are sprayed evenly creating random speckle patterns and point clouds from blade surfaces can be calculated by using speckle patterns based on the virtual stereo vision system. Secondly, boundary points are obtained in the way of varied step lengths according to curvature and are fitted to get a blade surface envelope with a cubic B-spline curve. Finally, the surface model of blades is established with the envelope curves and the point clouds. Experimental results show that the surface model of aircraft engine blades is fair and accurate.

Spatial reflection patterns of iridescent wings of male pierid butterflies: curved scales reflect at a wider angle than flat scales.

PubMed

Pirih, Primož; Wilts, Bodo D; Stavenga, Doekele G

2011-10-01

The males of many pierid butterflies have iridescent wings, which presumably function in intraspecific communication. The iridescence is due to nanostructured ridges of the cover scales. We have studied the iridescence in the males of a few members of Coliadinae, Gonepteryx aspasia, G. cleopatra, G. rhamni, and Colias croceus, and in two members of the Colotis group, Hebomoia glaucippe and Colotis regina. Imaging scatterometry demonstrated that the pigmentary colouration is diffuse whereas the structural colouration creates a directional, line-shaped far-field radiation pattern. Angle-dependent reflectance measurements demonstrated that the directional iridescence distinctly varies among closely related species. The species-dependent scale curvature determines the spatial properties of the wing iridescence. Narrow beam illumination of flat scales results in a narrow far-field iridescence pattern, but curved scales produce broadened patterns. The restricted spatial visibility of iridescence presumably plays a role in intraspecific signalling.

Constrained paths based on the Farey sequence in learning to juggle.

PubMed

Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji

2015-12-01

In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

A Health 'Kuznets' Curve'? Cross-Sectional and Longitudinal Evidence on Concentration Indices'.

PubMed

Costa-Font, Joan; Hernandez-Quevedo, Cristina; Sato, Azusa

2018-01-01

The distribution of income related health inequalities appears to exhibit changing patterns when both developing countries and developed countries are examined. This paper tests for the existence of a health Kuznets' curve; that is, an inverse U-shape pattern between economic developments (as measured by GDP per capita) and income-related health inequalities (as measured by concentration indices). We draw upon both cross sectional (the World Health Survey) and a long longitudinal (the European Community Household Panel survey) dataset. Our results suggest evidence of a health Kuznets' curve on per capita income. We find a polynomial association where inequalities decline when GDP per capita reaches a magnitude ranging between $26,000 and $38,700. That is, income-related health inequalities rise with GDP per capita, but tail off once a threshold level of economic development has been attained.

Contrast-enhanced magnetic resonance imaging of pulmonary lesions: description of a technique aiming clinical practice.

PubMed

Koenigkam-Santos, Marcel; Optazaite, Elzbieta; Sommer, Gregor; Safi, Seyer; Heussel, Claus Peter; Kauczor, Hans-Ulrich; Puderbach, Michael

2015-01-01

To propose a technique for evaluation of pulmonary lesions using contrast-enhanced MRI; to assess morphological patterns of enhancement and correlate quantitative analysis with histopathology. Thirty-six patients were prospectively studied. Volumetric-interpolated T1W images were obtained during consecutive breath holds after bolus triggered contrast injection. Volume coverage of first three acquisitions was limited (higher temporal resolution) and last acquisition obtained at 4th min. Two radiologists individually evaluated the patterns of enhancement. Region-of-interest-based signal intensity (SI)-time curves were created to assess quantitative parameters. Readers agreed moderately to substantially concerning lesions' enhancement pattern. SI-time curves could be created for all lesions. In comparison to benign, malignant lesions showed higher values of maximum enhancement, early peak, slope and 4th min enhancement. Early peak >15% showed 100% sensitivity to detect malignancy, maximum enhancement >40% showed 100% specificity. The proposed technique is robust, simple to perform and can be applied in clinical scenario. It allows visual evaluation of enhancement pattern/progression together with creation of SI-time curves and assessment of derived quantitative parameters. Perfusion analysis was highly sensitive to detect malignancy, in accordance to what is recommended by most recent guidelines on imaging evaluation of pulmonary lesions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantification of the fraction poorly deformable red blood cells using ektacytometry.

PubMed

Streekstra, G J; Dobbe, J G G; Hoekstra, A G

2010-06-21

We describe a method to obtain the fraction of poorly deformable red blood cells in a blood sample from the intensity pattern in an ektacytometer. In an ektacytometer red blood cells are transformed into ellipsoids by a shear flow between two transparent cylinders. The intensity pattern, due to a laser beam that is sent through the suspension, is projected on a screen. When measuring a healthy red blood cell population iso-intensity curves are ellipses with an axial ratio equal to that of the average red blood cell. In contrast poorly deformable cells result in circular iso-intensity curves. In this study we show that for mixtures of deformable and poorly deformable red blood cells, iso-intensity curves in the composite intensity pattern are neither elliptical nor circular but obtain cross-like shapes. We propose a method to obtain the fraction of poorly deformable red blood cells from those intensity patterns. Experiments with mixtures of poorly deformable and deformable red blood cells validate the method and demonstrate its accuracy. In a clinical setting our approach is potentially of great value for the detection of the fraction of sickle cells in blood samples of patients with sickle cell disease or to find a measure for the parasitemia in patients infected with malaria.

Learning builds on learning: Infants' use of native language sound patterns to learn words

PubMed Central

Graf Estes, Katharine

2014-01-01

The present research investigated how infants apply prior knowledge of environmental regularities to support new learning. The experiments tested whether infants could exploit experience with native language (English) phonotactic patterns to facilitate associating sounds with meanings during word learning. Fourteen-month-olds heard fluent speech that contained cues for detecting target words; they were embedded in sequences that occur across word boundaries. A separate group heard the target words embedded without word boundary cues. Infants then participated in an object label-learning task. With the opportunity to use native language patterns to segment the target words, infants subsequently learned the labels. Without this experience, infants failed. Novice word learners can take advantage of early learning about sounds scaffold lexical development. PMID:24980741

5 Myths about Classroom Technology: How Do We Integrate Digital Tools to Truly Enhance Learning?

ERIC Educational Resources Information Center

Renwick, Matt

2015-01-01

What's keeping your school behind the technology curve? Is it a fear of the unfamiliar? Expenses? Or some other myth? Have you considered how students with special needs or students learning a second language may benefit from using digital tools? If you've fallen for the perception that technology is too expensive, unnecessary for real learning,…

Implementing Machine Learning in the PCWG Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clifton, Andrew; Ding, Yu; Stuart, Peter

The Power Curve Working Group (www.pcwg.org) is an ad-hoc industry-led group to investigate the performance of wind turbines in real-world conditions. As part of ongoing experience-sharing exercises, machine learning has been proposed as a possible way to predict turbine performance. This presentation provides some background information about machine learning and how it might be implemented in the PCWG exercises.

Learning to Learn Differently

ERIC Educational Resources Information Center

Olsen, Trude Høgvold; Glad, Tone; Filstad, Cathrine

2018-01-01

Purpose: This paper aims to investigate whether the formal and informal learning patterns of community health-care nurses changed in the wake of a reform that altered their work by introducing new patient groups, and to explore whether conditions in the new workplaces facilitated or impeded shifts in learning patterns. Design/methodology/approach:…

Undirected learning styles and academic risk: Analysis of the impact of stress, strain and coping.

PubMed

Kimatian, Stephen; Lloyd, Sara; Berger, Jeffrey; Steiner, Lorraine; McKay, Robert; Schwengal, Deborah

2017-01-01

Learning style inventories used in conjunction with a measure of academic achievement consistently show an association of meaning directed learning patterns with academic success, but have failed to show a clear association of undirected learning styles with academic failure. Using survey methods with anesthesia residents, this study questioned whether additional assessment of factors related to stress, strain, and coping help to better define the association between undirected learning styles and academic risk. Pearson chi squared tests. 296 subjects were enrolled from eight institutions with 142 (48%) completing the study. American Board of Anesthesiologists In Training Examinations (ITE) percentiles (ITE%) were used as a measure of academic achievement. The Vermunt Inventory of Learning Styles (ILS) was used to identify four learning patterns and 20 strategies, and the Osipow Stress Inventory-Revised (OSI-R) was used as a measure of six scales of occupational stress, four of personal strain, and four coping resources. Two learning patterns had significant relationship with ITE scores. As seen in previous studies, Meaning Directed Learning was beneficial for academic achievement while Undirected Learning was the least beneficial. Higher scores on Meaning Directed Learning correlated positively with higher ITE scores while higher Undirected and lower Meaning Directed patterns related negatively to ITE%. OSI-R measures of stress, strain and coping indicated that residents with Undirected learning patterns had higher scores on three scales related to stress, and 4 related to strain, while displaying lower scores on two scales related to coping. Residents with higher Meaning Directed patterns scored lower on two scales of stress and two scales of strain, with higher scores on two scales for coping resources. Low Meaning Directed and high Undirected learning patterns correlated with lower ITE percentiles, higher scores for stress and strain, and lower coping resources. This association suggests that successful remediation of at-risk residents must address stress, strain and coping if long term academic improvement is expected. Further research to identify the value of stress, strain, and coping screening and education is warranted.

An electromyographic study of muscle relaxants in man.

PubMed

Suzuki, H; Kanayama, T; Nakagawa, H; Yazaki, S; Shiratsuchi, T

1975-05-01

Supramaximal paired stimuli were applied to the ulnar nerve, and the amplitude of the muscle action potential evoked in the abductor digiti minimi by the second member of the stimulus pair (test response) was compared with that evoked by the first component (conditioning response). The interval between the two components of the stimulus pair (the pair interval) was increased stepwise from 7 to 100 msec and a curve (recovery curve) was obtained by relating the changes in pair interval to the difference in amplitude of the test and conditioning responses. Alterations of the recovery curve (RC) during partial paralysis by muscle relaxants were investigated in healthy adult patients under the lightest plane of general anaesthesia. The control curve obtained in 32 subjects before the administration of a muscle relaxant drug was characterized by slight depressions at very short intervals of paired stimuli, followed by a slight potentiation at 20-100 msec. With non-depolarizing relaxants, RC altered to the characteristic pattern of potentiation at very short intervals of stimuli, followed by a notable depression at longer intervals. In depolarizing blocks with small doses of suxamethonium, the depression of RC at short intervals in the control was enhanced and the pattern of RC was different from that of non-depolarizing agents. When desensitization blocks were instigated by the i.v. administration of suxamethonium, the RC patterns were similar to those of competitive agents.

Description Of Scoliotic Deformity Pattern By Harmonic Functions

NASA Astrophysics Data System (ADS)

Drerup, Burkhard; Hierholzer, Eberhard

1989-04-01

Frontal radiographs of scoliotic deformity of the spine reveal a characteristic pattern of lateral deviation, lateral tilt and axial rotation of vertebrae. In order to study interrelations between deformation parameters 478 radiographs of idiopathic scolioses, 23 of scolioses after Wilms-tumor treatment and 18 of scolioses following poliomyelitis were digitized. From these the curves of lateral deviation, tilt and rotation are calculated and fitted by Fourier series. By restriction to the first harmonic, analysis reduces to the analysis of a single phase and amplitude for each curve. Justification of this simplification will be discussed. Results provide a general geometric description of scoliotic deformity.

Patterns and Rates of Learning in Two Problem-Based Learning Courses Using Outcome Based Assessment and Elaboration Theory

ERIC Educational Resources Information Center

Kuruganti, Usha; Needham, Ted; Zundel, Pierre

2012-01-01

The concept of "practice makes perfect" was examined in this work in the context of effective learning. Specifically, we wanted to know how much practice was needed for students to demonstrate mastery of learning outcomes. Student learning patterns in two different university courses that use a similar education approach involving…

Understanding Individual Patterns of Learning: Implications for the Well-Being of Students

ERIC Educational Resources Information Center

O'Toole, Linda

2008-01-01

This article analyses the link between learning and well-being from the perspective that it is important to take into account the individual patterns of how young people learn and to encourage ways in which they can learn how they learn. Consideration is first given to recent insights and research in education and the cognitive and natural…

Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus

PubMed Central

Smith, Jack W.; Everhart, J.E.; Dickson, W.C.; Knowler, W.C.; Johannes, R.S.

1988-01-01

Neural networks or connectionist models for parallel processing are not new. However, a resurgence of interest in the past half decade has occurred. In part, this is related to a better understanding of what are now referred to as hidden nodes. These algorithms are considered to be of marked value in pattern recognition problems. Because of that, we tested the ability of an early neural network model, ADAP, to forecast the onset of diabetes mellitus in a high risk population of Pima Indians. The algorithm's performance was analyzed using standard measures for clinical tests: sensitivity, specificity, and a receiver operating characteristic curve. The crossover point for sensitivity and specificity is 0.76. We are currently further examining these methods by comparing the ADAP results with those obtained from logistic regression and linear perceptron models using precisely the same training and forecasting sets. A description of the algorithm is included.

Automated Dermoscopy Image Analysis of Pigmented Skin Lesions

PubMed Central

Baldi, Alfonso; Quartulli, Marco; Murace, Raffaele; Dragonetti, Emanuele; Manganaro, Mario; Guerra, Oscar; Bizzi, Stefano

2010-01-01

Dermoscopy (dermatoscopy, epiluminescence microscopy) is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs), allowing a better visualization of surface and subsurface structures (from the epidermis to the papillary dermis). This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. In order to reduce the learning-curve of non-expert clinicians and to mitigate problems inherent in the reliability and reproducibility of the diagnostic criteria used in pattern analysis, several indicative methods based on diagnostic algorithms have been introduced in the last few years. Recently, numerous systems designed to provide computer-aided analysis of digital images obtained by dermoscopy have been reported in the literature. The goal of this article is to review these systems, focusing on the most recent approaches based on content-based image retrieval systems (CBIR). PMID:24281070

Star cell type core configuration for structural sandwich materials

DOEpatents

Christensen, Richard M.

1995-01-01

A new pattern for cellular core material used in sandwich type structural materials. The new pattern involves star shaped cells intermixed with hexagonal shaped cells. The new patterned cellular core material includes star shaped cells interconnected at points thereof and having hexagonal shape cells positioned adjacent the star points. The new pattern allows more flexibility and can conform more easily to curved shapes.

Volumetric characterization of human patellar cartilage matrix on phase contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Nagarajan, Mahesh B.; Checefsky, Walter A.; Coan, Paola; Diemoz, Paul C.; Hobbs, Susan K.; Huber, Markus B.; Wismüller, Axel

2015-03-01

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 +/- 0.06) and homogeneity (AUC = 0.82 +/- 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Learning with imperfectly labeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

Learning Under Stress: The Inverted-U-Shape Function Revisited

ERIC Educational Resources Information Center

Salehi, Basira; Cordero, M. Isabel; Sandi, Carmen

2010-01-01

Although the relationship between stress intensity and memory function is generally believed to follow an inverted-U-shaped curve, strikingly this phenomenon has not been demonstrated under the same experimental conditions. We investigated this phenomenon for rats' performance in a hippocampus-dependent learning task, the radial arm water maze…

Tale of the Tape: International Teaching Assistant Noticing during Videotaped Classroom Observations

ERIC Educational Resources Information Center

Williams, Gwendolyn M.; Case, Rod E.

2015-01-01

International teaching assistants face challenges in learning the norms for teaching in American universities. In order to address this learning curve this article describes a qualitative study of twenty international teaching assistants that examined how these participants viewed observations as part of their professional development. The study…

Implicit learning of non-spatial sequences in schizophrenia

PubMed Central

MARVEL, CHERIE L.; SCHWARTZ, BARBARA L.; HOWARD, DARLENE V.; HOWARD, JAMES H.

2006-01-01

Recent studies have reported abnormal implicit learning of sequential patterns in patients with schizophrenia. Because these studies were based on visuospatial cues, the question remained whether patients were impaired simply due to the demands of spatial processing. This study examined implicit sequence learning in 24 patients with schizophrenia and 24 healthy controls using a non-spatial variation of the serial reaction time test (SRT) in which pattern stimuli alternated with random stimuli on every other trial. Both groups showed learning by responding faster and more accurately to pattern trials than to random trials. Patients, however, showed a smaller magnitude of sequence learning. Both groups were unable to demonstrate explicit knowledge of the nature of the pattern, confirming that learning occurred without awareness. Clinical variables were not correlated with the patients' learning deficits. Patients with schizophrenia have a decreased ability to develop sensitivity to regularly occurring sequences of events within their environment. This type of deficit may affect an array of cognitive and motor functions that rely on the perception of event regularity. PMID:16248901

Seeing a straight line on a curved surface: decoupling of patterns from surfaces by single IT neurons

PubMed Central

Ratan Murty, N. Apurva

2016-01-01

We have no difficulty seeing a straight line drawn on a paper even when the paper is bent, but this inference is in fact nontrivial. Doing so requires either matching local features or representing the pattern after factoring out the surface shape. Here we show that single neurons in the monkey inferior temporal (IT) cortex show invariant responses to patterns across rigid and nonrigid changes of surfaces. We recorded neuronal responses to stimuli in which the pattern and the surrounding surface were varied independently. In a subset of neurons, we found pattern-surface interactions that produced similar responses to stimuli across congruent pattern and surface transformations. These interactions produced systematic shifts in curvature tuning of patterns when overlaid on convex and flat surfaces. Our results show that surfaces are factored out of patterns by single neurons, thereby enabling complex perceptual inferences. NEW & NOTEWORTHY We have no difficulty seeing a straight line on a curved piece of paper, but in fact, doing so requires decoupling the shape of the surface from the pattern itself. Here we report a novel form of invariance in the visual cortex: single neurons in monkey inferior temporal cortex respond similarly to congruent transformations of patterns and surfaces, in effect decoupling patterns from the surface on which they are overlaid. PMID:27733595

Learning new meanings for known words: Biphasic effects of prior knowledge.

PubMed

Fang, Xiaoping; Perfetti, Charles; Stafura, Joseph

2017-01-01

In acquiring word meanings, learners are often confronted by a single word form that is mapped to two or more meanings. For example, long after how to roller-"skate", one may learn that "skate" is also a kind of fish. Such learning of new meanings for familiar words involves two potentially contrasting processes, relative to new form-new meaning learning: 1) Form-based familiarity may facilitate learning a new meaning, and 2) meaning-based interference may inhibit learning a new meaning. We examined these two processes by having native English speakers learn new, unrelated meanings for familiar (high frequency) and less familiar (low frequency) English words, as well as for unfamiliar (novel or pseudo-) words. Tracking learning with cued-recall tasks at several points during learning revealed a biphasic pattern: higher learning rates and greater learning efficiency for familiar words relative to novel words early in learning and a reversal of this pattern later in learning. Following learning, interference from original meanings for familiar words was detected in a semantic relatedness judgment task. Additionally, lexical access to familiar words with new meanings became faster compared to their exposure controls, but no such effect occurred for less familiar words. Overall, the results suggest a biphasic pattern of facilitating and interfering processes: Familiar word forms facilitate learning earlier, while interference from original meanings becomes more influential later. This biphasic pattern reflects the co-activation of new and old meanings during learning, a process that may play a role in lexicalization of new meanings.

Combined effects of complex magnetic fields and agmatine for contextual fear learning deficits in rats.

PubMed

McKay, B E; Persinger, M A

2003-04-18

Acute post-training exposures to weak intensity theta-burst stimulation (TBS) patterned complex magnetic fields attenuated the magnitude of conditioned fear learning for contextual stimuli. A similar learning impairment was evoked in a linear and dose-dependent manner by pre-conditioning injections of the polyamine agmatine. The present study examined the hypothesis that whole-body applications of the TBS complex magnetic field pattern when co-administered with systemic agmatine treatment may combine to evoke impairments in contextual fear learning. Within minutes of 4 mg/kg agmatine injections, male Wistar rats were fear conditioned to contextual stimuli and immediately exposed for 30 min to the TBS patterned complex magnetic field or to sham conditions. TBS patterned complex magnetic field treatment was found to linearly summate with the contextual fear learning impairment evoked by agmatine treatment alone. Furthermore, we report for sham-treated rats, but not rats exposed to the synthetic magnetic field pattern, that the magnitude of learned fear decreased and the amount of variability in learning increased, as the K-index (a measure of change in intensity of the time-varying ambient geomagnetic field) increased during the 3-hr intervals over which conditioning and testing sessions were conducted.

Hydrologic Impacts of Oak Harvesting and Evaluation of the Modified Universal Soil Loss Equation

Treesearch

Charlette R. Epifanio; Michael J. Singer; Xiaohong Huang

1991-01-01

Two Sierra foothill watersheds were monitored to learn what effects selective oak removal would have on watershed hydrology and water quality. We also used the data to generate sediment rating curves and evaluate the modified universal soil loss equation (MUSLE). Annual sediment rating curves better accounted for the variability in precipitation events from year to...

What Does a Graphical Representation Mean for Students at the Beginning of Function Teaching?

ERIC Educational Resources Information Center

Yavuz, Ilyas

2010-01-01

This study examines how students in the early stages of learning about the concept of functions, describe a curve and, in particular, evaluate the appropriateness of their argument about the representation of a function. Students are offered a message game which is related to a curve drawn on a coordinate system, representing an "imaginary…

Longitudinal Examination of Procrastination and Anxiety, and Their Relation to Self-Efficacy for Self- Regulated Learning: Latent Growth Curve Modeling

ERIC Educational Resources Information Center

Yerdelen, Sündüs; McCaffrey, Adam; Klassen, Robert M.

2016-01-01

This study investigated the longitudinal association between students' anxiety and procrastination and the relation of self-efficacy for self-regulation to these constructs. Latent Growth Curve Modeling was used to analyze data gathered from 182 undergraduate students (134 female, 48 male) at 4 times during a semester. Our results showed that…

The "U" Curve Hypothesis: A Framework for Making Sense of Learning to Teach in Diverse Settings

ERIC Educational Resources Information Center

Birrell, James R.; Tinney, Mari Vawn

2008-01-01

Experiences in this research study started in 1991 before many teacher educators were aware of the "?U"? curve hypothesis or predictable stages of culture shock and the recognizable stages used on the path to gaining intercultural competence. This study of student teachers is used here as an illustration of what happens when teachers are…

The Sociocultural Adjustment Trajectory of International University Students and the Role of University Structures: A Qualitative Investigation

ERIC Educational Resources Information Center

Coles, Rebecca; Swami, Viren

2012-01-01

The present research explores the sociocultural adjustment of international students and the role played by university structures in the process. The adjustment process of international students has been modelled in psychological literature as a U-curve, a learning curve and most recently as a long, uneven and unending process of change. Yet,…

Applying active learning to supervised word sense disambiguation in MEDLINE.

PubMed

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models.

Applying active learning to supervised word sense disambiguation in MEDLINE

PubMed Central

Chen, Yukun; Cao, Hongxin; Mei, Qiaozhu; Zheng, Kai; Xu, Hua

2013-01-01

Objectives This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models. Methods We developed support vector machine (SVM) classifiers to disambiguate 197 ambiguous terms and abbreviations in the MSH WSD collection. Three different uncertainty sampling-based active learning algorithms were implemented with the SVM classifiers and were compared with a passive learner (PL) based on random sampling. For each ambiguous term and each learning algorithm, a learning curve that plots the accuracy computed from the test set as a function of the number of annotated samples used in the model was generated. The area under the learning curve (ALC) was used as the primary metric for evaluation. Results Our experiments demonstrated that active learners (ALs) significantly outperformed the PL, showing better performance for 177 out of 197 (89.8%) WSD tasks. Further analysis showed that to achieve an average accuracy of 90%, the PL needed 38 annotated samples, while the ALs needed only 24, a 37% reduction in annotation effort. Moreover, we analyzed cases where active learning algorithms did not achieve superior performance and identified three causes: (1) poor models in the early learning stage; (2) easy WSD cases; and (3) difficult WSD cases, which provide useful insight for future improvements. Conclusions This study demonstrated that integrating active learning strategies with supervised WSD methods could effectively reduce annotation cost and improve the disambiguation models. PMID:23364851

Medical learning curves and the Kantian ideal.

PubMed

Le Morvan, P; Stock, B

2005-09-01

A hitherto unexamined problem for the "Kantian ideal" that one should always treat patients as ends in themselves, and never only as a means to other ends, is explored in this paper. The problem consists of a prima facie conflict between this Kantian ideal and the reality of medical practice. This conflict arises because, at least presently, medical practitioners can only acquire certain skills and abilities by practising on live, human patients, and given the inevitability and ubiquity of learning curves, this learning requires some patients to be treated only as a means to this end. A number of ways of attempting to establish the compatibility of the Kantian Ideal with the reality of medical practice are considered. Each attempt is found to be unsuccessful. Accordingly, until a way is found to reconcile them, we conclude that the Kantian ideal is inconsistent with the reality of medical practice.

Medical learning curves and the Kantian ideal

PubMed Central

Le Morvan, P; Stock, B

2005-01-01

A hitherto unexamined problem for the "Kantian ideal" that one should always treat patients as ends in themselves, and never only as a means to other ends, is explored in this paper. The problem consists of a prima facie conflict between this Kantian ideal and the reality of medical practice. This conflict arises because, at least presently, medical practitioners can only acquire certain skills and abilities by practising on live, human patients, and given the inevitability and ubiquity of learning curves, this learning requires some patients to be treated only as a means to this end. A number of ways of attempting to establish the compatibility of the Kantian Ideal with the reality of medical practice are considered. Each attempt is found to be unsuccessful. Accordingly, until a way is found to reconcile them, we conclude that the Kantian ideal is inconsistent with the reality of medical practice. PMID:16131552

Recurrence plot analysis of nonstationary data: the understanding of curved patterns.

PubMed

Facchini, A; Kantz, H; Tiezzi, E

2005-08-01

Recurrence plots of the calls of the Nomascus concolor (Western black crested gibbon) and Hylobates lar (White-handed gibbon) show characteristic circular, curved, and hyperbolic patterns superimposed to the main temporal scale of the signal. It is shown that these patterns are related to particular nonstationarities in the signal. Some of them can be reproduced by artificial signals like frequency modulated sinusoids and sinusoids with time divergent frequency. These modulations are too faint to be resolved by conventional time-frequency analysis with similar precision. Therefore, recurrence plots act as a magnifying glass for the detection of multiple temporal scales in slightly modulated signals. The detected phenomena in these acoustic signals can be explained in the biomechanical context by taking in account the role of the muscles controlling the vocal folds.

Three-Dimensional Ultrasonic Imaging Of The Cornea

NASA Technical Reports Server (NTRS)

Heyser, Rrichar C.; Rooney, James A.

1988-01-01

Proposed technique generates pictures of curved surfaces. Object ultrasonically scanned in raster pattern generated by scanning transmitter/receiver. Receiver turned on at frequent intervals to measure depth variations of scanned object. Used for medical diagnoses by giving images of small curved objects as cornea. Adaptable to other types of reflection measurementsystems such as sonar and radar.

Do Curved Reaching Movements Emerge from Competing Perceptions? A Reply to van der Wel et al. (2009)

ERIC Educational Resources Information Center

Spivey, Michael J.; Dale, Rick; Knoblich, Guenther; Grosjean, Marc

2010-01-01

Spivey, Grosjean, and Knoblich (2005) reported smoothly curved reaching movements, via computer-mouse tracking, which suggested a continuously evolving flow of distributed lexical activation patterns into motor movement during a phonological competitor task. For example, when instructed to click the "candy," participants' mouse-cursor trajectories…

The Role of Statistical Learning and Working Memory in L2 Speakers' Pattern Learning

ERIC Educational Resources Information Center

McDonough, Kim; Trofimovich, Pavel

2016-01-01

This study investigated whether second language (L2) speakers' morphosyntactic pattern learning was predicted by their statistical learning and working memory abilities. Across three experiments, Thai English as a Foreign Language (EFL) university students (N = 140) were exposed to either the transitive construction in Esperanto (e.g., "tauro…

Political Learning among Youth: Exploring Patterns of Students' First Political Awakening

ERIC Educational Resources Information Center

Solhaug, Trond; Kristensen, Niels Nørgaard

2013-01-01

This article focuses on students' first political learning and explores the research question, "What dynamic patterns of political learning can be explored among a sample of young, diverse Danish students' first political interests?" The authors use theories of learning in their analytical approach to students' stories. A group of 10…

Poorer Phonetic Perceivers Show Greater Benefit in Phonetic-Phonological Speech Learning

ERIC Educational Resources Information Center

Ingvalson, Erin M.; Barr, Allison M.; Wong, Patrick C. M.

2013-01-01

Purpose: Previous research has demonstrated that native English speakers can learn lexical tones in word context (pitch-to-word learning), to an extent. However, learning success depends on learners' pre-training sensitivity to pitch patterns. The aim of this study was to determine whether lexical pitch-pattern training given before lexical…

Learning Patterns as Criterion for Forming Work Groups in 3D Simulation Learning Environments

ERIC Educational Resources Information Center

Maria Cela-Ranilla, Jose; Molías, Luis Marqués; Cervera, Mercè Gisbert

2016-01-01

This study analyzes the relationship between the use of learning patterns as a grouping criterion to develop learning activities in the 3D simulation environment at University. Participants included 72 Spanish students from the Education and Marketing disciplines. Descriptive statistics and non-parametric tests were conducted. The process was…

Temporal Patterns and Dynamics of E-Learning Usage in Medical Education

ERIC Educational Resources Information Center

Panzarasa, Pietro; Kujawski, Bernard; Hammond, Edward J.; Roberts, C. Michael

2016-01-01

Despite the increasing popularity of e-learning systems across a variety of educational programmes, there is relatively little understanding of how students and trainees distribute their learning efforts over time. This study aimed to analyse the usage patterns of an e-learning resource designed to support specialty training. Data were collected…

Principal curve detection in complicated graph images

NASA Astrophysics Data System (ADS)

Liu, Yuncai; Huang, Thomas S.

2001-09-01

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

Independent voluntary correction and savings in locomotor learning.

PubMed

Leech, Kristan A; Roemmich, Ryan T

2018-06-14

People can acquire new walking patterns in many different ways. For example, we can change our gait voluntarily in response to instruction or adapt by sensing our movement errors. Here we investigated how acquisition of a new walking pattern through simultaneous voluntary correction and adaptive learning affected the resulting motor memory of the learned pattern. We studied adaptation to split-belt treadmill walking with and without visual feedback of stepping patterns. As expected, visual feedback enabled faster acquisition of the new walking pattern. However, upon later re-exposure to the same split-belt perturbation, participants exhibited similar motor memories whether they had learned with or without visual feedback. Participants who received feedback did not re-engage the mechanism used to accelerate initial acquisition of the new walking pattern to similarly accelerate subsequent relearning. These findings reveal that voluntary correction neither benefits nor interferes with the ability to save a new walking pattern over time. © 2018. Published by The Company of Biologists Ltd.

What We Can Learn from the Data: A Multiple-Case Study Examining Behavior Patterns by Students with Different Characteristics in Using a Serious Game

ERIC Educational Resources Information Center

Liu, Min; Lee, Jaejin; Kang, Jina; Liu, Sa

2016-01-01

Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our…

A Study of Learning in the Operations of a Viscous Damped Traversing Unit.

DTIC Science & Technology

1978-06-01

Finally I would like to express special appreciation to my wife, Donna Pardue Robinson, and my children, Kristin, Keith and Stephanie for their...indication of learning. Bahrick, Fitts and Briggs dealt with learning curves in a 1957 article which supported their earlier work. They used the same data...Olof and Kaare Rodahl, Textbook of Work Physiology, New York: McGraw-Hill Book Compnay, 1970. 2. Bahrick, H. P., F. M. Fitts and G. E. Briggs , "Learning

Muscle Fiber Type Composition and Knee Extension Isometric Strength Fatigue Patterns in Power- and Endurance-Trained Males.

ERIC Educational Resources Information Center

Kroll, Walter; And Others

1980-01-01

There is a degree of uniqueness in fatigue patterns, particularly between different levels of absolute maximum strength. Caution should be used when analyzing fatigue curves among subjects with unspecified strength levels. (CJ)

An evidence-based virtual reality training program for novice laparoscopic surgeons.

PubMed

Aggarwal, Rajesh; Grantcharov, Teodor P; Eriksen, Jens R; Blirup, Dorthe; Kristiansen, Viggo B; Funch-Jensen, Peter; Darzi, Ara

2006-08-01

To develop an evidence-based virtual reality laparoscopic training curriculum for novice laparoscopic surgeons to achieve a proficient level of skill prior to participating in live cases. Technical skills for laparoscopic surgery must be acquired within a competency-based curriculum that begins in the surgical skills laboratory. Implementation of this program necessitates the definition of the validity, learning curves and proficiency criteria on the training tool. The study recruited 40 surgeons, classified into experienced (performed >100 laparoscopic cholecystectomies) or novice groups (<10 laparoscopic cholecystectomies). Ten novices and 10 experienced surgeons were tested on basic tasks, and 11 novices and 9 experienced surgeons on a procedural module for dissection of Calot triangle. Performance of the 2 groups was assessed using time, error, and economy of movement parameters. All basic tasks demonstrated construct validity (Mann-Whitney U test, P < 0.05), and learning curves for novices plateaued at a median of 7 repetitions (Friedman's test, P < 0.05). Expert surgeons demonstrated a learning rate at a median of 2 repetitions (P < 0.05). Performance on the dissection module demonstrated significant differences between experts and novices (P < 0.002); learning curves for novice subjects plateaued at the fourth repetition (P < 0.05). Expert benchmark criteria were defined for validated parameters on each task. A competency-based training curriculum for novice laparoscopic surgeons has been defined. This can serve to ensure that junior trainees have acquired prerequisite levels of skill prior to entering the operating room, and put them directly into practice.

Da Vinci© Skills Simulator™: is an early selection of talented console surgeons possible?

PubMed

Meier, Mark; Horton, Kevin; John, Hubert

2016-12-01

To investigate whether the learning curve of robotic surgery simulator training depends on the probands' characteristics, such as age and prior experience, we conducted a study of six distinct proband groups, using the da Vinci Skills Simulator: experienced urological robotic surgeons, surgeons with experience as da Vinci tableside assistants, urological surgeons with laparoscopic experience, urological surgeons without laparoscopic experience, and complete novices aged 25 and younger and 40 and older. The results showed that all experienced robotic surgeons reached expert level (>90 %, as defined previously in the literature) within the first three repetitions and remained on a high level of performance. All other groups performed worse. Tableside assistants, laparoscopically experienced surgeons, and younger novices showed a better performance in all exercises than surgeons without laparoscopic experience and older novices. A linear mixed-effects model analysis demonstrated no significant difference in learning curves between proband groups in all exercises except the RW1 exercise for the younger proband group. In summary, we found that performance in robotic surgery, measured by performance scores in three virtual simulator modules using the EndoWrist techniques, was dependent on age and prior experience with robotic and laparoscopic surgery. However, and most importantly, the learning curve was not significantly affected by these factors. This suggests that the da Vinci Skills Simulator™ is a useful practice tool for everyone learning or performing robotic surgery, and that early selection of talented surgeons is neither possible nor necessary.

Increased reward in ankle robotics training enhances motor control and cortical efficiency in stroke.

PubMed

Goodman, Ronald N; Rietschel, Jeremy C; Roy, Anindo; Jung, Brian C; Diaz, Jason; Macko, Richard F; Forrester, Larry W

2014-01-01

Robotics is rapidly emerging as a viable approach to enhance motor recovery after disabling stroke. Current principles of cognitive motor learning recognize a positive relationship between reward and motor learning. Yet no prior studies have established explicitly whether reward improves the rate or efficacy of robotics-assisted rehabilitation or produces neurophysiologic adaptations associated with motor learning. We conducted a 3 wk, 9-session clinical pilot with 10 people with chronic hemiparetic stroke, randomly assigned to train with an impedance-controlled ankle robot (anklebot) under either high reward (HR) or low reward conditions. The 1 h training sessions entailed playing a seated video game by moving the paretic ankle to hit moving onscreen targets with the anklebot only providing assistance as needed. Assessments included paretic ankle motor control, learning curves, electroencephalograpy (EEG) coherence and spectral power during unassisted trials, and gait function. While both groups exhibited changes in EEG, the HR group had faster learning curves (p = 0.05), smoother movements (p

An algorithm for the classification of mRNA patterns in eosinophilic esophagitis: Integration of machine learning.

PubMed

Sallis, Benjamin F; Erkert, Lena; Moñino-Romero, Sherezade; Acar, Utkucan; Wu, Rina; Konnikova, Liza; Lexmond, Willem S; Hamilton, Matthew J; Dunn, W Augustine; Szepfalusi, Zsolt; Vanderhoof, Jon A; Snapper, Scott B; Turner, Jerrold R; Goldsmith, Jeffrey D; Spencer, Lisa A; Nurko, Samuel; Fiebiger, Edda

2018-04-01

Diagnostic evaluation of eosinophilic esophagitis (EoE) remains difficult, particularly the assessment of the patient's allergic status. This study sought to establish an automated medical algorithm to assist in the evaluation of EoE. Machine learning techniques were used to establish a diagnostic probability score for EoE, p(EoE), based on esophageal mRNA transcript patterns from biopsies of patients with EoE, gastroesophageal reflux disease and controls. Dimensionality reduction in the training set established weighted factors, which were confirmed by immunohistochemistry. Following weighted factor analysis, p(EoE) was determined by random forest classification. Accuracy was tested in an external test set, and predictive power was assessed with equivocal patients. Esophageal IgE production was quantified with epsilon germ line (IGHE) transcripts and correlated with serum IgE and the T h 2-type mRNA profile to establish an IGHE score for tissue allergy. In the primary analysis, a 3-class statistical model generated a p(EoE) score based on common characteristics of the inflammatory EoE profile. A p(EoE) ≥ 25 successfully identified EoE with high accuracy (sensitivity: 90.9%, specificity: 93.2%, area under the curve: 0.985) and improved diagnosis of equivocal cases by 84.6%. The p(EoE) changed in response to therapy. A secondary analysis loop in EoE patients defined an IGHE score of ≥37.5 for a patient subpopulation with increased esophageal allergic inflammation. The development of intelligent data analysis from a machine learning perspective provides exciting opportunities to improve diagnostic precision and improve patient care in EoE. The p(EoE) and the IGHE score are steps toward the development of decision trees to define EoE subpopulations and, consequently, will facilitate individualized therapy. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Nitric oxide synthase inhibition depresses the height of the cerebral blood flow-pressure autoregulation curve during moderate hypotension.

PubMed

Jones, Stephen C; Easley, Kirk A; Radinsky, Carol R; Chyatte, Douglas; Furlan, Anthony J; Perez-Trepichio, Alejandro D

2003-09-01

Variations in the height of the CBF response to hypotension have been described recently in normal animals. The authors evaluated the effects of nitric oxide synthase (NOS) inhibition on these variations in height using laser Doppler flowmetry in 42 anesthetized (halothane and N2O) male Sprague-Dawley rats prepared with a superfused closed cranial window. In four groups (time control, enantiomer control, NOS inhibition, and reinfusion control) exsanguination to MABPs from 100 to 40 mm Hg was used to produce autoregulatory curves. For each curve the lower limit of autoregulation (the MABP at the first decrease in CBF) was identified; the pattern of autoregulation was classified as "peak" (15% increase in %CBF), "classic" (plateau with a decrease at the lower limit of autoregulation), or "none" (15% decrease in %CBF); and the autoregulatory height as the %CBF at 70 mm Hg (%CBF(70)) was determined. NOS inhibition decreased %CBF(70) in the NOS inhibition group (P = 0.014), in the control (combined time and enantiomer control) group (P = 0.015), and in the reinfusion control group (P = 0.025). NOS inhibition via superfusion depressed the autoregulatory pattern (P = 0.02, McNemar test on changes in autoregulatory pattern) compared with control (P = 0.375). Analysis of covariance showed that changes induced by NOS inhibition in the parameters of autoregulatory height are not related to changes in the lower limit, but are strongly (P < 0.001) related to each other. NOS inhibition depressed the autoregulatory pattern, decreasing the seemingly paradoxical increase in CBF as blood pressure decreases. These results suggest that nitric oxide increases CBF near the lower limit and augments the hypotensive portion of the autoregulatory curve.

On the mean profiles of radio pulsars - II. Reconstruction of complex pulsar light curves and other new propagation effects

NASA Astrophysics Data System (ADS)

Hakobyan, H. L.; Beskin, V. S.; Philippov, A. A.

2017-08-01

Our previous paper outlined the general aspects of the theory of radio light curve and polarization formation for pulsars. We predicted the one-to-one correspondence between the tilt of the linear polarization position angle of the the circular polarization. However, some of the radio pulsars indicate a clear deviation from that correlation. In this paper, we apply the theory of the radio wave propagation in the pulsar magnetosphere for the analysis of individual effects leading to these deviations. We show that within our theory the circular polarization of a given mode can switch its sign, without the need to introduce a new radiation mode or other effects. Moreover, we show that the generation of different emission modes on different altitudes can explain pulsars, that presumably have the X-O-X light-curve pattern, different from what we predict. General properties of radio emission within our propagation theory are also discussed. In particular, we calculate the intensity patterns for different radiation altitudes and present light curves for different observer viewing angles. In this context we also study the light curves and polarization profiles for pulsars with interpulses. Further, we explain the characteristic width of the position angle curves by introducing the concept of a wide emitting region. Another important feature of radio polarization profiles is the shift of the position angle from the centre, which in some cases demonstrates a weak dependence on the observation frequency. Here we demonstrate that propagation effects do not necessarily imply a significant frequency-dependent change of the position angle curve.

Curve Appeal: Exploring Individual Differences in Preference for Curved Versus Angular Objects

PubMed Central

Cotter, Katherine N.; Bertamini, Marco; Palumbo, Letizia; Vartanian, Oshin

2017-01-01

A preference for smooth curvature, as opposed to angularity, is a well-established finding for lines, two-dimensional shapes, and complex objects, but little is known about individual differences. We used two-dimensional black-and-white shapes—randomly generated irregular polygons, and arrays of circles and hexagons—and measured many individual differences, including artistic expertise, personality, and cognitive style. As expected, people preferred curved over angular stimuli, and people’s degree of curvature preference correlated across the two sets of shapes. Multilevel models showed varying patterns of interaction between shape and individual differences. For the irregular polygons, people higher in artistic expertise or openness to experience showed a greater preference for curvature. This pattern was not evident for the arrays of circles and hexagons. We discuss the results in relation to the nature of the stimuli, and we conclude that individual differences do play a role in moderating the preference for smooth curvature. PMID:28491269

Star cell type core configuration for structural sandwich materials

DOEpatents

Christensen, R.M.

1995-08-01

A new pattern for cellular core material used in sandwich type structural materials is disclosed. The new pattern involves star shaped cells intermixed with hexagonal shaped cells. The new patterned cellular core material includes star shaped cells interconnected at points thereof and having hexagonal shape cells positioned adjacent the star points. The new pattern allows more flexibility and can conform more easily to curved shapes. 3 figs.

Classification of Uxo by Principal Dipole Polarizability

NASA Astrophysics Data System (ADS)

Kappler, K. N.

2010-12-01

Data acquired by multiple-Transmitter, multiple-receiver time-domain electromagnetic devices show great potential for determining the geometric and compositional information relating to near surface conductive targets. Here is presented an analysis of data from one such system; the Berkeley Unexploded-ordnance Discriminator (BUD) system. BUD data are succinctly reduced by processing the multi-static data matrices to obtain magnetic dipole polarizability matrices for data from each time gate. When viewed over all time gates, the projections of the data onto the principal polar axes yield so-called polarizability curves. These curves are especially well suited to discriminating between subsurface conductivity anomalies which correspond to objects of rotational symmetry and irregularly shaped objects. The curves have previously been successfully employed as library elements in a pattern recognition scheme aimed at discriminating harmless scrap metal from dangerous intact unexploded ordnance. However, previous polarizability-curve matching methods have only been applied at field sites which are known a priori to be contaminated by a single type of ordnance, and furthermore, the particular ordnance present in the subsurface was known to be large. Thus signal amplitude was a key element in the discrimination process. The work presented here applies feature-based pattern classification techniques to BUD field data where more than 20 categories of object are present. Data soundings from a calibration grid at the Yuma, AZ proving ground are used in a cross validation study to calibrate the pattern recognition method. The resultant method is then applied to a Blind Test Grid. Results indicate that when lone UXO are present and SNR is reasonably high, Polarizability Curve Matching successfully discriminates UXO from scrap metal when a broad range of objects are present.

Placement of central venous port catheters and peripherally inserted central catheters in the routine clinical setting of a radiology department: analysis of costs and intervention duration learning curve.

PubMed

Rotzinger, Roman; Gebauer, Bernhard; Schnapauff, Dirk; Streitparth, Florian; Wieners, Gero; Grieser, Christian; Freyhardt, Patrick; Hamm, Bernd; Maurer, Martin H

2017-12-01

Background Placement of central venous port catheters (CVPS) and peripherally inserted central catheters (PICC) is an integral component of state-of-the-art patient care. In the era of increasing cost awareness, it is desirable to have more information to comprehensively assess both procedures. Purpose To perform a retrospective analysis of interventional radiologic implantation of CVPS and PICC lines in a large patient population including a cost analysis of both methods as well as an investigation the learning curve in terms of the interventions' durations. Material and Methods All CVPS and PICC line related interventions performed in an interventional radiology department during a three-year period from January 2011 to December 2013 were examined. Documented patient data included sex, venous access site, and indication for CVPS or PICC placement. A cost analysis including intervention times was performed based on the prorated costs of equipment use, staff costs, and expenditures for disposables. The decrease in intervention duration in the course of time conformed to the learning curve. Results In total, 2987 interventions were performed by 16 radiologists: 1777 CVPS and 791 PICC lines. An average implantation took 22.5 ± 0.6 min (CVPS) and 10.1 ± 0.9 min (PICC lines). For CVPS, this average time was achieved by seven radiologists newly learning the procedures after performing 20 CVPS implantations. Total costs per implantation were €242 (CVPS) and €201 (PICC lines). Conclusion Interventional radiologic implantations of CVPS and PICC lines are well-established procedures, easy to learn by residents, and can be implanted at low costs.

Evaluation of the learning curve for thulium laser enucleation of the prostate with the aid of a simulator tool but without tutoring: comparison of two surgeons with different levels of endoscopic experience.

PubMed

Saredi, Giovanni; Pirola, Giacomo Maria; Pacchetti, Andrea; Lovisolo, Jon Alexander; Borroni, Giacomo; Sembenini, Federico; Marconi, Alberto Mario

2015-06-09

The aim of this study was to determine the learning curve for thulium laser enucleation of the prostate (ThuLEP) for two surgeons with different levels of urological endoscopic experience. From June 2012 to August 2013, ThuLEP was performed on 100 patients in our institution. We present the results of a prospective evaluation during which we analyzed data related to the learning curves for two surgeons of different levels of experience. The prostatic adenoma volumes ranged from 30 to 130 mL (average 61.2 mL). Surgeons A and B performed 48 and 52 operations, respectively. Six months after surgery, all patients were evaluated with the International Prostate Symptom Score questionnaire, uroflowmetry, and prostate-specific antigen test. Introduced in 2010, ThuLEP consists of blunt enucleation of the prostatic apex and lobes using the sheath of the resectoscope. This maneuver allows clearer visualization of the enucleation plane and precise identification of the prostatic capsule. These conditions permit total resection of the prostatic adenoma and coagulation of small penetrating vessels, thereby reducing the laser emission time. Most of the complications in this series were encountered during morcellation, which in some cases was performed under poor vision because of venous bleeding due to surgical perforation of the capsule during enucleation. Based on this analysis, we concluded that it is feasible for laser-naive urologists with endoscopic experience to learn to perform ThuLEP without tutoring. Those statements still require further validation in larger multicentric study cohort by several surgeon. The main novelty during the learning process was the use of a simulator that faithfully reproduced all of the surgical steps in prostates of various shapes and volumes.

Microinvasive Glaucoma Stent (MIGS) Surgery With Concomitant Phakoemulsification Cataract Extraction: Outcomes and the Learning Curve.

PubMed

Al-Mugheiry, Toby S; Cate, Heidi; Clark, Allan; Broadway, David C

2017-07-01

To evaluate learning effects with respect to outcomes of a microinvasive glaucoma stent (MIGS) inserted during cataract surgery in glaucoma patients. Single surgeon, observational cohort study of 25 consecutive Ivantis Hydrus microstent insertions, with a minimum follow-up of 12 months. A learning curve analysis was performed by assessing hypotensive effect, adverse effects, and surgical procedure duration, with respect to consecutive case number. Success was defined with respect to various intraocular pressure (IOP) targets (21, 18, 15 mm Hg) and reduction in required antiglaucoma medications. Complete success was defined as achieving target IOP without antiglaucoma therapy. No clinically significant adverse events or learning effects were identified, although surgical time reduced with consecutive case number. Mean follow-up was 16.8 months. At final follow-up the mean IOP for all eyes was reduced from 18.1 (±3.6) mm Hg [and a simulated untreated value of 25.9 (±5.2) mm Hg] to 15.3 (±2.2) mm Hg (P=0.007; <0.0001) and the mean number of topical antiglaucoma medications was reduced from 1.96 (±0.96) to 0.04 (±0.20) (P<0.0001). Complete success (IOP<21 mm Hg, no medications) was 96% at final follow-up. Complete success (IOP<18 mm Hg, no medications) was 80% at final follow-up, but only 32% with a target IOP of <15 mm Hg (no medications). No significant learning curve effects were observed for a trained surgeon with respect to MIGS microstent insertion performed at the time of cataract surgery. Adjunctive MIGS surgery was successful in lowering IOP to <18 mm Hg and reducing/abolishing the requirement for antiglaucoma medication in eyes with open-angle glaucoma, but less successful at achieving low IOP levels (<15 mm Hg).

On the cost of approximating and recognizing a noise perturbed straight line or a quadratic curve segment in the plane. [central processing units

NASA Technical Reports Server (NTRS)

Cooper, D. B.; Yalabik, N.

1975-01-01

Approximation of noisy data in the plane by straight lines or elliptic or single-branch hyperbolic curve segments arises in pattern recognition, data compaction, and other problems. The efficient search for and approximation of data by such curves were examined. Recursive least-squares linear curve-fitting was used, and ellipses and hyperbolas are parameterized as quadratic functions in x and y. The error minimized by the algorithm is interpreted, and central processing unit (CPU) times for estimating parameters for fitting straight lines and quadratic curves were determined and compared. CPU time for data search was also determined for the case of straight line fitting. Quadratic curve fitting is shown to require about six times as much CPU time as does straight line fitting, and curves relating CPU time and fitting error were determined for straight line fitting. Results are derived on early sequential determination of whether or not the underlying curve is a straight line.

Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

NASA Astrophysics Data System (ADS)

Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; Ernastuti

2016-06-01

An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

Seeing the Errors You Feel Enhances Locomotor Performance but Not Learning.

PubMed

Roemmich, Ryan T; Long, Andrew W; Bastian, Amy J

2016-10-24

In human motor learning, it is thought that the more information we have about our errors, the faster we learn. Here, we show that additional error information can lead to improved motor performance without any concomitant improvement in learning. We studied split-belt treadmill walking that drives people to learn a new gait pattern using sensory prediction errors detected by proprioceptive feedback. When we also provided visual error feedback, participants acquired the new walking pattern far more rapidly and showed accelerated restoration of the normal walking pattern during washout. However, when the visual error feedback was removed during either learning or washout, errors reappeared with performance immediately returning to the level expected based on proprioceptive learning alone. These findings support a model with two mechanisms: a dual-rate adaptation process that learns invariantly from sensory prediction error detected by proprioception and a visual-feedback-dependent process that monitors learning and corrects residual errors but shows no learning itself. We show that our voluntary correction model accurately predicted behavior in multiple situations where visual feedback was used to change acquisition of new walking patterns while the underlying learning was unaffected. The computational and behavioral framework proposed here suggests that parallel learning and error correction systems allow us to rapidly satisfy task demands without necessarily committing to learning, as the relative permanence of learning may be inappropriate or inefficient when facing environments that are liable to change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Patterns in Clinical Students' Self-Regulated Learning Behavior: A Q-Methodology Study

ERIC Educational Resources Information Center

Berkhout, Joris J.; Teunissen, Pim W.; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P.; Jaarsma, Debbie A.

2017-01-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in…

An Examination into the Learning Pattern Preferences of Students in Special Education

ERIC Educational Resources Information Center

Thone, Jaime L.

2013-01-01

As educational professionals strive to help students become efficient and effective learners, they must assist in the development of student learning strategies and a greater understanding of the learning process. The purpose of this study was to analyze and compare the learning pattern preferences of middle and high school students in general…

Relationships between Hong Kong Students' Perceptions of the Learning Environment and Their Learning Patterns in Post-Secondary Education

ERIC Educational Resources Information Center

Law, Dennis C. S.; Meyer, Jan H. F.

2011-01-01

The present study aims to analyse the complex relationships between the relevant constructs of students' demographic background, perceptions, learning patterns and (proxy measures of) learning outcomes in order to delineate the possible direct, indirect, or spurious effects among them. The analytical methodology is substantively framed against the…

Defining the learning curve of laparoendoscopic single-site Heller myotomy.

PubMed

Ross, Sharona B; Luberice, Kenneth; Kurian, Tony J; Paul, Harold; Rosemurgy, Alexander S

2013-08-01

Initial outcomes suggest laparoendoscopic single-site (LESS) Heller myotomy with anterior fundoplication provides safe, efficacious, and cosmetically superior outcomes relative to conventional laparoscopy. This study was undertaken to define the learning curve of LESS Heller myotomy with anterior fundoplication. One hundred patients underwent LESS Heller myotomy with anterior fundoplication. Symptom frequency and severity were scored using a Likert scale (0 = never/not bothersome to 10 = always/very bothersome). Symptom resolution, additional trocars, and complications were compared among patient quartiles. Median data are presented. Preoperative frequency/severity scores were: dysphagia = 10/8 and regurgitation = 8/7. Additional trocars were placed in 12 patients (10%), of whom all were in the first two quartiles. Esophagotomy/gastrotomy occurred in three patients. Postoperative complications occurred in 9 per cent. No conversions to "open" operations occurred. Length of stay was 1 day. Postoperative frequency/severity scores were: dysphagia = 2/0 and regurgitation = 0/0; scores were less than before myotomy (P < 0.001). There were no apparent scars, except where additional trocars were placed. LESS Heller myotomy with anterior fundoplication well palliates symptoms of achalasia with no apparent scar. Placement of additional trocars only occurred early in the experience. For surgeons proficient with the conventional laparoscopic approach, the learning curve of LESS Heller myotomy with anterior fundoplication is short and safe, because proficiency is quickly attained.

Learning curve of thyroid fine-needle aspiration biopsy.

PubMed

Penín, Manuel; Martín, M Ángeles; San Millán, Beatriz; García, Juana

2017-12-01

Fine-needle aspiration biopsy (FNAB) is the reference procedure for thyroid nodule evaluation. Its main limitation are inadequate samples, which should be less than 20%. To analyze the learning curve of the procedure by comparing the results of a non-experienced endocrinologist (endocrinologist 2) to those of an experienced one (endocrinologist 1). Sixty FNABs were analyzed from February to June 2016. Each endocrinologist made 2punctures of every nodule in a random order. This order and the professional making every puncture were unknown to the pathologist who examined the samples. Endocrinologist 1 had a higher percentage of diagnoses than endocrinologist 2 (82% vs. 72%, P=.015). In the first 20 FNABs, the difference between both physicians was remarkable and statistically significant (80% vs. 50%, P=.047). In the following 20 FNABs, the difference narrowed and was not statistically significant (90% vs. 65%, P=.058). In the final 20 FNABs, the difference was minimal and not statistically significant (75% vs. 70%, P=.723). The learning curve of ultrasound-guided FNAB may be completed in a suitable environment by performing it at least 60 times. Although the guidelines recommend at least 3punctures per nodule, 2are enough to achieve an accurate percentage of diagnoses. Copyright © 2017 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

Incremental Implicit Learning of Bundles of Statistical Patterns

PubMed Central

Qian, Ting; Jaeger, T. Florian; Aslin, Richard N.

2016-01-01

Forming an accurate representation of a task environment often takes place incrementally as the information relevant to learning the representation only unfolds over time. This incremental nature of learning poses an important problem: it is usually unclear whether a sequence of stimuli consists of only a single pattern, or multiple patterns that are spliced together. In the former case, the learner can directly use each observed stimulus to continuously revise its representation of the task environment. In the latter case, however, the learner must first parse the sequence of stimuli into different bundles, so as to not conflate the multiple patterns. We created a video-game statistical learning paradigm and investigated 1) whether learners without prior knowledge of the existence of multiple “stimulus bundles” — subsequences of stimuli that define locally coherent statistical patterns — could detect their presence in the input, and 2) whether learners are capable of constructing a rich representation that encodes the various statistical patterns associated with bundles. By comparing human learning behavior to the predictions of three computational models, we find evidence that learners can handle both tasks successfully. In addition, we discuss the underlying reasons for why the learning of stimulus bundles occurs even when such behavior may seem irrational. PMID:27639552

The SBRT database initiative of the German Society for Radiation Oncology (DEGRO): patterns of care and outcome analysis of stereotactic body radiotherapy (SBRT) for liver oligometastases in 474 patients with 623 metastases.

PubMed

Andratschke, N; Alheid, H; Allgäuer, M; Becker, G; Blanck, O; Boda-Heggemann, J; Brunner, T; Duma, M; Gerum, S; Guckenberger, M; Hildebrandt, G; Klement, R J; Lewitzki, V; Ostheimer, C; Papachristofilou, A; Petersen, C; Schneider, T; Semrau, R; Wachter, S; Habermehl, D

2018-03-13

The intent of this pooled analysis as part of the German society for radiation oncology (DEGRO) stereotactic body radiotherapy (SBRT) initiative was to analyze the patterns of care of SBRT for liver oligometastases and to derive factors influencing treated metastases control and overall survival in a large patient cohort. From 17 German and Swiss centers, data on all patients treated for liver oligometastases with SBRT since its introduction in 1997 has been collected and entered into a centralized database. In addition to patient and tumor characteristics, data on immobilization, image guidance and motion management as well as dose prescription and fractionation has been gathered. Besides dose response and survival statistics, time trends of the aforementioned variables have been investigated. In total, 474 patients with 623 liver oligometastases (median 1 lesion/patient; range 1–4) have been collected from 1997 until 2015. Predominant histologies were colorectal cancer (n = 213 pts.; 300 lesions) and breast cancer (n = 57; 81 lesions). All centers employed an SBRT specific setup. Initially, stereotactic coordinates and CT simulation were used for treatment set-up (55%), but eventually were replaced by CBCT guidance (28%) or more recently robotic tracking (17%). High variance in fraction (fx) number (median 1 fx; range 1–13) and dose per fraction (median: 18.5 Gy; range 3–37.5 Gy) was observed, although median BED remained consistently high after an initial learning curve. Median follow-up time was 15 months; median overall survival after SBRT was 24 months. One- and 2-year treated metastases control rate of treated lesions was 77% and 64%; if maximum isocenter biological equivalent dose (BED) was greater than 150 Gy EQD2Gy, it increased to 83% and 70%, respectively. Besides radiation dose colorectal and breast histology and motion management methods were associated with improved treated metastases control. After an initial learning curve with regards to total cumulative doses, consistently high biologically effective doses have been employed translating into high local tumor control at 1 and 2 years. The true impact of histology and motion management method on treated metastases control deserve deeper analysis. Overall survival is mainly influenced by histology and metastatic tumor burden.

Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder

PubMed Central

Mercado, Eduardo; Church, Barbara A.; Coutinho, Mariana V. C.; Dovgopoly, Alexander; Lopata, Christopher J.; Toomey, Jennifer A.; Thomeer, Marcus L.

2015-01-01

Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets. PMID:26157368

The art and learning patterns of knowing in nursing.

PubMed

Baixinho, Cristina Lavareda; Ferraz, Isabel Carvalho Beato; Ferreira, Óscar Manuel Ramos; Rafael, Helga Marilia da Silva

2014-12-01

Objective To identify the perception of the students about the use of art as a pedagogical strategy in learning the patterns of knowing in nursing; to identify the dimensions of each pattern valued in the analysis of pieces of art. Method Descriptive mixed study. Data collection used a questionnaire applied to 31 nursing students. Results In the analysis of the students' discourse, it was explicit that empirical knowledge includes scientific knowledge, tradition and nature of care. The aesthetic knowledge implies expressiveness, subjectivity and sensitivity. Self-knowledge, experience, reflective attitude and relationships with others are the subcategories of personal knowledge and the moral and ethics support ethical knowledge. Conclusion It is possible to learn patterns of knowledge through art, especially the aesthetic, ethical and personal. It is necessary to investigate further pedagogical strategies that contribute to the learning patterns of nursing knowledge.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

PubMed

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Learning new meanings for known words: Biphasic effects of prior knowledge

PubMed Central

Fang, Xiaoping; Perfetti, Charles; Stafura, Joseph

2017-01-01

In acquiring word meanings, learners are often confronted by a single word form that is mapped to two or more meanings. For example, long after how to roller-“skate”, one may learn that “skate” is also a kind of fish. Such learning of new meanings for familiar words involves two potentially contrasting processes, relative to new form-new meaning learning: 1) Form-based familiarity may facilitate learning a new meaning, and 2) meaning-based interference may inhibit learning a new meaning. We examined these two processes by having native English speakers learn new, unrelated meanings for familiar (high frequency) and less familiar (low frequency) English words, as well as for unfamiliar (novel or pseudo-) words. Tracking learning with cued-recall tasks at several points during learning revealed a biphasic pattern: higher learning rates and greater learning efficiency for familiar words relative to novel words early in learning and a reversal of this pattern later in learning. Following learning, interference from original meanings for familiar words was detected in a semantic relatedness judgment task. Additionally, lexical access to familiar words with new meanings became faster compared to their exposure controls, but no such effect occurred for less familiar words. Overall, the results suggest a biphasic pattern of facilitating and interfering processes: Familiar word forms facilitate learning earlier, while interference from original meanings becomes more influential later. This biphasic pattern reflects the co-activation of new and old meanings during learning, a process that may play a role in lexicalization of new meanings. PMID:29399593

Reference Curve for the Mean Uterine Artery Pulsatility Index in Singleton Pregnancies.

PubMed

Weichert, Alexander; Hagen, Andreas; Tchirikov, Michael; Fuchs, Ilka B; Henrich, Wolfgang; Entezami, Michael

2017-05-01

Doppler sonography of the uterine artery (UA) is done to monitor pregnancies, because the detected flow patterns are useful to draw inferences about possible disorders of trophoblast invasion. Increased resistance in the UA is associated with an increased risk of preeclampsia and/or intrauterine growth restriction (IUGR) and perinatal mortality. In the absence of standardized figures, the normal ranges of the various available reference curves sometimes differ quite substantially from one another. The causes for this are differences in the flow patterns of the UA depending on the position of the pulsed Doppler gates as well as branching of the UA. Because of the discrepancies between the different reference curves and the practical problems this poses for guideline recommendations, we thought it would be useful to create our own reference curves for Doppler measurements of the UA obtained from a singleton cohort under standardized conditions. This retrospective cohort study was carried out in the Department of Obstetrics of the Charité - Universitätsmedizin Berlin, the Department for Obstetrics and Prenatal Medicine of the University Hospital Halle (Saale) and the Center for Prenatal Diagnostics and Human Genetics Kurfürstendamm 199. Available datasets from the three study locations were identified and reference curves were generated using the LMS method. Measured values were correlated with age of gestation, and a cubic model and Box-Cox power transformation (L), the median (M) and the coefficient of variation (S) were used to smooth the curves. 103 720 Doppler examinations of the UA carried out in singleton pregnancies from the 11th week of gestation (10 + 1 GW) were analyzed. The mean pulsatility index (Mean PI) showed a continuous decline over the course of pregnancy, dropping to a plateau of around 0.84 between the 23rd and 27th GW, after which it decreased again. Age of gestation, placental position, position of pulsed Doppler gates and branching of the UA can all change the flow pattern. The mean pulsatility index (Mean PI) showed a continuous decrease over time. There were significant differences between our data and alternative reference curves. A system of classifying Doppler studies and a reference curve adapted to the current technology are urgently required to differentiate better between physiological and pathological findings.

Millennials Invading: Building Training for Today's Admissions Counselors

ERIC Educational Resources Information Center

Barnds, W. Kent

2009-01-01

As chief admissions officer at two small colleges, the author has been responsible, in part, for ensuring that entry-level admissions counselors are trained properly. He learned through trial and error, and has adapted his methods to be increasingly sensitive to the learning curve of new employees. His thoughts about training new admissions…

Learning, Retention, and Forgetting of Newton's Third Law throughout University Physics

ERIC Educational Resources Information Center

Sayre, Eleanor C.; Franklin, Scott V.; Dymek, Stephanie; Clark, Jessica; Sun, Yifei

2012-01-01

We present data from a between-student study on student response to questions on Newton's third law given in two introductory calculus-based physics classes (Mechanics and Electromagnetism) at a large northeastern university. Construction of a response curve reveals subtle dynamics in student learning not capturable by pretesting and post-testing.…

Home Literacy Environment and Head Start Children's Language Development: The Role of Approaches to Learning

ERIC Educational Resources Information Center

Meng, Christine

2015-01-01

Research Findings: This study examined whether approaches to learning moderate the association between home literacy environment and English receptive vocabulary development. The Head Start Family and Child Experiences Survey (2003 cohort) was used for analysis. Latent growth curve modeling was utilized to test a quadratic model of English…

Relevance Vector Machine and Support Vector Machine Classifier Analysis of Scanning Laser Polarimetry Retinal Nerve Fiber Layer Measurements

PubMed Central

Bowd, Christopher; Medeiros, Felipe A.; Zhang, Zuohua; Zangwill, Linda M.; Hao, Jiucang; Lee, Te-Won; Sejnowski, Terrence J.; Weinreb, Robert N.; Goldbaum, Michael H.

2010-01-01

Purpose To classify healthy and glaucomatous eyes using relevance vector machine (RVM) and support vector machine (SVM) learning classifiers trained on retinal nerve fiber layer (RNFL) thickness measurements obtained by scanning laser polarimetry (SLP). Methods Seventy-two eyes of 72 healthy control subjects (average age = 64.3 ± 8.8 years, visual field mean deviation =−0.71 ± 1.2 dB) and 92 eyes of 92 patients with glaucoma (average age = 66.9 ± 8.9 years, visual field mean deviation =−5.32 ± 4.0 dB) were imaged with SLP with variable corneal compensation (GDx VCC; Laser Diagnostic Technologies, San Diego, CA). RVM and SVM learning classifiers were trained and tested on SLP-determined RNFL thickness measurements from 14 standard parameters and 64 sectors (approximately 5.6° each) obtained in the circumpapillary area under the instrument-defined measurement ellipse (total 78 parameters). Tenfold cross-validation was used to train and test RVM and SVM classifiers on unique subsets of the full 164-eye data set and areas under the receiver operating characteristic (AUROC) curve for the classification of eyes in the test set were generated. AUROC curve results from RVM and SVM were compared to those for 14 SLP software-generated global and regional RNFL thickness parameters. Also reported was the AUROC curve for the GDx VCC software-generated nerve fiber indicator (NFI). Results The AUROC curves for RVM and SVM were 0.90 and 0.91, respectively, and increased to 0.93 and 0.94 when the training sets were optimized with sequential forward and backward selection (resulting in reduced dimensional data sets). AUROC curves for optimized RVM and SVM were significantly larger than those for all individual SLP parameters. The AUROC curve for the NFI was 0.87. Conclusions Results from RVM and SVM trained on SLP RNFL thickness measurements are similar and provide accurate classification of glaucomatous and healthy eyes. RVM may be preferable to SVM, because it provides a Bayesian-derived probability of glaucoma as an output. These results suggest that these machine learning classifiers show good potential for glaucoma diagnosis. PMID:15790898

Preliminary Results and Learning Curve of the Minimally Invasive Chevron Akin Operation for Hallux Valgus.

PubMed

Jowett, Charlie R J; Bedi, Harvinder S

Minimally invasive surgery is increasing in popularity. It is relevant in hallux valgus surgery owing to the potential for reduced disruption of the soft tissues and improved wound healing. We present our results and assess the learning curve of the minimally invasive Chevron Akin operation for hallux valgus. A total of 120 consecutive feet underwent minimally invasive Chevron Akin for symptomatic hallux valgus, of which 14 were excluded. They were followed up for a mean of 25 (range 18 to 38) months. The patients were clinically assessed using the American Orthopaedic Foot and Ankle Society score. Complications and patient satisfaction were recorded. The radiographs were analyzed and measurements recorded for hallux valgus and intermetatarsal angle correction. The mean age of the patients undergoing surgery was 55 (range 25 to 81) years. Of the 78 patients, 76 (97.4%) were female and 2 (2.6%) were male; 28 (35.9%) cases were bilateral. The mean American Orthopaedic Foot and Ankle Society score improved from 56 (range 23 to 76) preoperatively to 87 (range 50 to 100) postoperatively (p < .001). The mean hallux valgus and intermetatarsal angles preoperatively were 29.7° (range 12° to 46°) and 14.0° (range 8° to 20°). The corresponding postoperative angles were 10.3° (range 0° to 25°) and 7.6° (range 3° to 15°; p < .001). The patients were satisfied with the results of surgery in 87% of cases (92 of 106). The incidence of reoperation was 14% (15 of 106). These are the only reported results for this technique. They display a steep associated learning curve. However, the results are promising, and the learning curve is comparable to that for open hallux valgus surgery. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Learning curves and perioperative outcomes after endoscopic enucleation of the prostate: a comparison between GreenLight 532-nm and holmium lasers.

PubMed

Peyronnet, Benoit; Robert, Grégoire; Comat, Vincent; Rouprêt, Morgan; Gomez-Sancha, Fernando; Cornu, Jean-Nicolas; Misrai, Vincent

2017-06-01

To compare the learning curves, perioperative and early functional outcomes after HoLEP and GreenLEP. Data from the first 100 consecutive cases treated by GreenLEP and HoLEP by two surgeons were prospectively collected from dedicated databases and analysed retrospectively. En-bloc GreenLEP and two-lobar HoLEP enucleations were conducted using the GreenLight HPS™ 2090 laser and Lumenis™ holmium laser. Patients' characteristics, perioperative outcomes and functional outcomes after 1, 3 and 6 months were compared between groups. Total energy delivered and operative times were significantly shorter for GreenLEP (58 vs. 110 kJ, p < 0.0001; 60 vs. 90 min, p < 0.0001). Operative time reached a plateau after 30 procedures in each group. Length of catheterization and hospital stay were significantly shorter in the HoLEP group (2 vs. 1 day, p < 0.0001; 2 vs. 1 day, p < 0.0001). Postoperative complications were comparable between GreenLEP and HoLEP (19 vs. 25 %; p = 0.13). There was a greater increase of Q max at 3 months and a greater IPSS decrease at 1 month for GreenLEP, whereas decreases in IPSS and IPSS-Q8 at 6 months were greater for HoLEP. Transient stress urinary incontinence was comparable between both groups (6 vs. 9 % at 3 months; p = 0.42). Pentafecta was achieved in four consecutive patients after the 18th and the 40th procedure in the GreenLEP and HoLEP group, respectively. Learning curves ranged from 14 to 30 cases for GreenLEP and 22 to 40 cases for HoLEP. Learning curves of GreenLEP and HoLEP provided roughly similar peri-operative and short-term functional outcomes.

Assessment of quality outcomes for robotic pancreaticoduodenectomy: identification of the learning curve.

PubMed

Boone, Brian A; Zenati, Mazen; Hogg, Melissa E; Steve, Jennifer; Moser, Arthur James; Bartlett, David L; Zeh, Herbert J; Zureikat, Amer H

2015-05-01

Quality assessment is an important instrument to ensure optimal surgical outcomes, particularly during the adoption of new surgical technology. The use of the robotic platform for complex pancreatic resections, such as the pancreaticoduodenectomy, requires close monitoring of outcomes during its implementation phase to ensure patient safety is maintained and the learning curve identified. To report the results of a quality analysis and learning curve during the implementation of robotic pancreaticoduodenectomy (RPD). A retrospective review of a prospectively maintained database of 200 consecutive patients who underwent RPD in a large academic center from October 3, 2008, through March 1, 2014, was evaluated for important metrics of quality. Patients were analyzed in groups of 20 to minimize demographic differences and optimize the ability to detect statistically meaningful changes in performance. Robotic pancreaticoduodenectomy. Optimization of perioperative outcome parameters. No statistical differences in mortality rates or major morbidity were noted during the study. Statistical improvements in estimated blood loss and conversions to open surgery occurred after 20 cases (600 mL vs 250 mL [P = .002] and 35.0% vs 3.3% [P < .001], respectively), incidence of pancreatic fistula after 40 cases (27.5% vs 14.4%; P = .04), and operative time after 80 cases (581 minutes vs 417 minutes [P < .001]). Complication rates, lengths of stay, and readmission rates showed continuous improvement that did not reach statistical significance. Outcomes for the last 120 cases (representing optimized metrics beyond the learning curve) included a mean operative time of 417 minutes, median estimated blood loss of 250 mL, a conversion rate of 3.3%, 90-day mortality of 3.3%, a clinically significant (grade B/C) pancreatic fistula rate of 6.9%, and a median length of stay of 9 days. Continuous assessment of quality metrics allows for safe implementation of RPD. We identified several inflexion points corresponding to optimization of performance metrics for RPD that can be used as benchmarks for surgeons who are adopting this technology.

Nasoenteral feeding tube placement by nurses using an electromagnetic guidance system (with video).

PubMed

Mathus-Vliegen, Elisabeth M H; Duflou, Ann; Spanier, Marcel B W; Fockens, Paul

2010-04-01

The early institution of feeding in patients who need postpyloric feeding tubes is often hampered by a limited availability of endoscopists experienced in safe tube positioning. To test the feasibility of having nurses place postpyloric feeding tubes by using a universal path finding system device. Prospective study. Academic hospital. The success rate and learning curve of a senior nurse placing postpyloric feeding tubes in 50 patients was studied, followed by a study in 160 patients on the success rates and learning curves of 4 inexperienced nurses instructed by the senior nurse. Finally, the success rate of postpyloric feeding tube placement by the senior nurse in 50 critically ill patients was investigated. Postpyloric feeding tube positioning by nurses using an electromagnetic universal path-finding system device enabling them to follow the path of the tip of the feeding tube on a monitor screen. Success was defined by postpyloric positioning of the feeding tube. The ultimate aim was to reach at least the duodenojejunal flexure. In the first part, the senior nurse was successful in 72% of cases. There was a clear learning curve. In the second part, the 4 newly instructed nurses had a success rate of 89.4% without an evident learning curve. In the third part, successful feeding tube positioning was achieved in 78% of critically ill patients. Of the 217 successfully positioned tubes, 74% reached at least the duodenojejunal flexure. In half of the unsuccessful cases, an explanation for the failure was found at endoscopy. No complications were seen. The generalization to less-specialized hospitals should be investigated. Postpyloric positioning of feeding tubes by nurses at the bedside without endoscopy is feasible and safe. Nurses may take over some of the tasks of doctors in a time of high endoscopic needs. Copyright 2010 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer.

PubMed

Lendínez-Cano, G; Osman García, I; Congregado Ruiz, C B; Conde Sánchez, J M; Medina López, R A

2018-03-07

To analyse the learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer. We evaluated 32 consecutive patients treated in our department for metastatic renal cancer with tyrosine kinase inhibitors (pazopanib or sunitinib) as first-line treatment between September 2012 and November 2015. We retrospectively analysed this sample. We measured the time to the withdrawal of the first-line treatment, the time to progression and overall survival using Kaplan-Meier curves. The learning curve was analysed with the cumulative sum (CUSUM) methodology. In our series, the median time to the withdrawal of the first-line treatment was 11 months (95% CI 4.9-17.1). The mean time to progression was 30.4 months (95% CI 22.7-38.1), and the mean overall survival was 34.9 months (95% CI 27.8-42). By applying the CUSUM methodology, we obtained a graph for the CUSUM value of the time to withdrawal of the first-line treatment (CUSUM TW), observing 3 well-differentiated phases: phase 1 or initial learning phase (1-15), phase 2 (16-26) in which the management of the drug progressively improved and phase 3 (27-32) of maximum experience or mastery of the management of these drugs. The number of treated patients needed to achieve the proper management of these patients was estimated at 15. Despite the limitations of the sample size and follow-up time, we estimated (in 15 patients) the number needed to reach the necessary experience in the management of these patients with tyrosine kinase inhibitors. We observed no relationship between the time to the withdrawal of the first-line treatment for any cause and progression. Copyright © 2018 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

A comparison of hysteroscopic mechanical tissue removal with bipolar electrical resection for the management of endometrial polyps in an ambulatory care setting: preliminary results.

PubMed

Pampalona, Jennifer Rovira; Bastos, Maria Degollada; Moreno, Gemma Mancebo; Pust, Andrea Buron; Montesdeoca, Gemma Escribano; Guerra Garcia, Angel; Pruñonosa, Juan Carles Mateu; Collado, Ramon Carreras; Torras, Pere Bresco

2015-01-01

To assess and compare efficacy, pain, and the learning curve associated with diagnostic therapeutic hysteroscopy using mechanical tissue removal versus bipolar electrical resection in the management of endometrial polyps in an ambulatory care setting. A randomized controlled clinical trial (Canadian Task Force classification I). Hospital de Igulada, Barcelona, Spain. A total of 133 patients diagnosed with endometrial polyp(s) were included and randomly assigned to 1 of the 2 hysteroscopic methods. Criteria assessed were total hysteroscopy time, full polypectomy procedure time, pain experienced by patients, and learning curve of staff in training. The average time to perform total hysteroscopy using the mechanical tissue removal system (TRUCLEAR 5.0 System; Smith & Nephew Inc., Andover, MD) was 6 minutes 49 seconds versus 11 minutes 37 seconds required for the bipolar electrosurgery system (GYNECARE VERSAPOINT; Ethicon Inc, Somerville, NJ) (p < .01). Results for complete polypectomy time favored the TRUCLEAR System at 3 minutes 7 seconds over the VERSAPOINT System at 8 minutes 25 seconds (p < .01). If a successful procedure is predicated on access to cavity, visualization, and complete resection and excision of endometrial polyp, the mechanical TRUCLEAR Tissue Removal System shows a higher success rate than the VERSAPOINT Bipolar Electrosurgery System at 92% and 77%, respectively. Analysis of pain using the visual analog scale revealed no significant differences between the 2 techniques (p > .05). A study of the residents' learning curve showed a higher level of autonomy with hysteroscopy using the TRUCLEAR Tissue Removal System with which residents showed a higher level of confidence compared with hysteroscopy with the VERSAPOINT Bipolar Electrosurgery System. In hysteroscopic polypectomy, the mechanical tissue removal system was significantly faster, achieved a greater success rate for complete polypectomy, and required a shorter learning curve from staff being trained in the management of endometrial polyps when compared with bipolar electrical resection. Copyright © 2015 AAGL. Published by Elsevier Inc. All rights reserved.

[The monophasic pattern in oral glucose tolerance test as a predictive risk factor of type 2 diabetes in obese paediatric patients].

PubMed

Herrera-Martínez, Aura D; Enes, Patricia; Martín-Frías, María; Roldán, Belén; Yelmo, Rosa; Barrio, Raquel

2017-10-01

The onset of obesity at young ages is strongly associated with the early development of type 2diabetes (T2D). The shape of the curves of glucose and insulin curves during an oral glucose tolerance test (OGTT) could predict the risk of developing T2D. To analyse the morphology of the OGTT and determine T2D risk factors in a mainly Caucasian population of children and adolescents. Observational retrospective study including 588 patients (309 males, 279 females) with a mean age of 11.1±2years, and of whom 90.3% were Caucasian. Risk factors for T2D were compared in patients with a monophasic or biphasic pattern during the performance of an OGTT, as well as anthropometric and biochemical variables, insulin resistance, and beta-cell function. The shape of the glucose curve was monophasic in 50.2% of patients (50.8% male), biphasic in 48.5% (47.6% males), and indeterminate in 1.3%. The monophasic pattern showed lower insulin-sensitivity and worse beta-cell function. Patients with a biphasic pattern had a higher BMI, waist circumference, and blood pressure, although the results were not significant. Latin-American patients had significantly lower serum glucose levels with higher insulin levels during the OGTT. The pattern of response to an OGTT reflects different metabolic phenotypes. Paediatric patients with a biphasic pattern have lower risk-profiling for T2D. The performing of an OGTT could be useful to implement early intervention strategies in children and adolescents with obesity, in order to prevent the development of pre-diabetes or T2D. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

The Study of Two-Dimensional Oscillations Using a Smartphone Acceleration Sensor: Example of Lissajous Curves

ERIC Educational Resources Information Center

Tuset-Sanchis, Luis; Castro-Palacio, Juan C.; Gómez-Tejedor, José A.; Manjón, Francisco J.; Monsoriu, Juan A.

2015-01-01

A smartphone acceleration sensor is used to study two-dimensional harmonic oscillations. The data recorded by the free android application, Accelerometer Toy, is used to determine the periods of oscillation by graphical analysis. Different patterns of the Lissajous curves resulting from the superposition of harmonic motions are illustrated for…

Precipitation records and flood-producing storms in Cheyenne, Wyoming

USGS Publications Warehouse

Lindner-Lunsford, J. B.

1988-01-01

Annual maximum precipitation data for Cheyenne, Wyoming, are presented for the years 1871-1986 for durations of 5, 10, 15, and 30 minutes and 1, 2, and 24 hours. Precipitation-frequency curves are developed on the basis of data collected before 1985; a second set of curves are developed on the basis of data collected through 1986. The data are plotted and analyzed three times, assuming: (1) The data are described by a Gumbel distribution; (2) the logarithms of the data are described by a Gumbel distribution; and (3) the logarithms of the data are described by a Pearson Type III distribution. The inclusion of data for the large storm of August 1, 1985, had the most noticeable effect on the prediction of the magnitude of storms of long average recurrence intervals for the 1-, 2-, and 24-hour durations. Seven intensity-duration curves were calculated for the August 1, 1985 storm. For durations greater than 30 minutes, the observed curve indicates greater intensity than do five of the seven calculated curves. Dimensionless hyetographs were developed for 10 flood-producing storms that have occurred in the Cheyenne area since 1903. The pattern index (integral of the dimensionless hyetograph curve) for the storm of August 1, 1985, is 3 standard deviations lower than the mean of the pattern indices for the remaining 9 storms, indicating that the distribution of precipitation with time for the August 1, 1985, storm was outside the normal range for Cheyenne. (USGS)

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

PubMed

Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

Testing the limits of long-distance learning: Learning beyond a three-segment window

PubMed Central

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones since long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ('sh') and triggered a suffix that was either [−su] or [−∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. PMID:22303815

The selective serotonin reuptake inhibitor, escitalopram, enhances inhibition of prepotent responding and spatial reversal learning

PubMed Central

Brown, Holden D.; Amodeo, Dionisio A.; Sweeney, John A.; Ragozzino, Michael E.

2011-01-01

Previous findings indicate treatment with a selective serotonin reuptake inhibitor (SSRI) facilitates behavioral flexibility when conditions require inhibition of a learned response pattern. The present experiment investigated whether acute treatment with the SSRI, escitalopram, affects behavioral flexibility when conditions require inhibition of a naturally-biased response pattern (elevated conflict test) and/or reversal of a learned response pattern (spatial reversal learning). An additional experiment was carried out to determine whether escitalopram, at doses that affected behavioral flexibility, also reduced anxiety as tested in the elevated plus-maze. In each experiment, Long-Evans rats received an intraperitoneal injection of either saline or escitalopram (0.03, 0.3 or 1.0 mg/kg) 30 minutes prior to behavioral testing. Escitalopram, at all doses tested, enhanced acquisition in the elevated conflict test, but did not affect performance in the elevated plus-maze. Escitalopram (0.3 and 1.0 mg/kg) did not alter acquisition of the spatial discrimination, but facilitated reversal learning. In the elevated conflict and spatial reversal learning test, escitalopram enhanced the ability to maintain the relevant strategy after being initially selected. The present findings suggest that enhancing serotonin transmission with a SSRI facilitates inhibitory processes when conditions require a shift away from either a naturally-biased response pattern or a learned choice pattern. PMID:22219222

Characterization of mechanical unfolding intermediates of membrane proteins by coarse grained molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Yamada, Tatsuya; Mitaku, Shigeki; Yamato, Takahisa

2018-01-01

Single-molecule force spectroscopy by atomic force microscopy allows us to get insight into the mechanical unfolding of membrane proteins, and a typical experiment exhibits characteristic patterns on the force distance curves. The origin of these patterns, however, has not been fully understood yet. We performed coarse-grained simulation of the forced unfolding of halorodopsin, reproduced the characteristic features of the experimental force distance curves. A further examination near the membrane-water interface indicated the existence of a motif for the force peak formation, i.e., the occurrence of hydrophobic residues in the upper interface region and hydrophilic residues below the lower interface region.

Detection of discontinuous patterns in spontaneous brain activity of neonates and fetuses.

PubMed

Vairavan, Srinivasan; Eswaran, Hari; Haddad, Naim; Rose, Douglas F; Preissl, Hubert; Wilson, James D; Lowery, Curtis L; Govindan, Rathinaswamy B

2009-11-01

The discontinuous patterns in neonatal magnetoencephalographic (MEG) data are quantified with a novel Hilbert phase (HP) based approach. The expert neurologists' scores were used as the gold standard. The performance of this approach was analyzed using a receiver operating characteristic (ROC) curve, and it was compared with two other approaches, namely spectral ratio (SR) and discrete wavelet transform (DWT) that have been proposed for the detection of discontinuous patterns in neonatal EEG. The area under the ROC curve (AUC) was used as a performance measure. AUCs obtained for SR, HP, and DWT were 0.87, 0.80, and 0.56, respectively. Although the performance of HP was lower than SR, it carries information about the frequency content of the signal that helps to distinguish brain patterns from artifacts such as cardiac residuals. Based on this property, the HP approach was extended to fetal MEG data. Further, using the frequency property of the HP approach, burst duration and interburst interval were computed for the discontinuous patterns detected and they are in agreement with reported values.

Convection currents in a water calorimeter.

PubMed

Schulz, R J; Weinhous, M S

1985-10-01

A flexible, temperature-regulated water calorimeter has been constructed containing two pairs of thermistor sensors at depths of 6.23 and 10.0 cm. It may be irradiated by vertical or horizontal beams, and operated at temperatures in the range from 3 to 40 degrees C. When irradiated at 30 degrees C with a vertically downward 19 MeV electron beam, the responses of the proximal and midline thermistors were in accordance with the depth-dose curve. When irradiated horizontally, the initial patterns of temperature rise were the same, but after about 30 s (4 Gy) the rate of temperature rise decreased at the proximal thermistors and increased at the midline thermistors. Shortly after irradiation, the temperature curve and increased at the midline thermistors. Shortly after irradiation, the temperature curve of the midline thermistors crossed that for the proximal thermistors, a pattern that suggested the presence of convection currents. To test this hypothesis, the calorimeter was operated at 4 degrees C. The temperature patterns for horizontal irradiation became the same as those obtained with vertical beams, thus demonstrating the production of convection currents in water at a temperature of 30 degrees C for temperature gradients as small as 10(-3) degrees C cm-1.

Convergence and divergence of neurocognitive patterns in schizophrenia and depression.

PubMed

Liang, Sugai; Brown, Matthew R G; Deng, Wei; Wang, Qiang; Ma, Xiaohong; Li, Mingli; Hu, Xun; Juhas, Michal; Li, Xinmin; Greiner, Russell; Greenshaw, Andrew J; Li, Tao

2018-02-01

Neurocognitive impairments are frequently observed in schizophrenia and major depressive disorder (MDD). However, it remains unclear whether reported neurocognitive abnormalities could objectively identify an individual as having schizophrenia or MDD. The current study included 220 first-episode patients with schizophrenia, 110 patients with MDD and 240 demographically matched healthy controls (HC). All participants performed the short version of the Wechsler Adult Intelligence Scale-Revised in China; the immediate and delayed logical memory of the Wechsler Memory Scale-Revised in China; and seven tests from the computerized Cambridge Neurocognitive Test Automated Battery to evaluate neurocognitive performance. The three-class AdaBoost tree-based ensemble algorithm was employed to identify neurocognitive endophenotypes that may distinguish between subjects in the categories of schizophrenia, depression and HC. Hierarchical cluster analysis was applied to further explore the neurocognitive patterns in each group. The AdaBoost algorithm identified individual's diagnostic class with an average accuracy of 77.73% (80.81% for schizophrenia, 53.49% for depression and 86.21% for HC). The average area under ROC curve was 0.92 (0.96 in schizophrenia, 0.86 in depression and 0.92 in HC). Hierarchical cluster analysis revealed for MDD and schizophrenia, convergent altered neurocognition patterns related to shifting, sustained attention, planning, working memory and visual memory. Divergent neurocognition patterns for MDD and schizophrenia related to motor speed, general intelligence, perceptual sensitivity and reversal learning were identified. Neurocognitive abnormalities could predict whether the individual has schizophrenia, depression or neither with relatively high accuracy. Additionally, the neurocognitive features showed promise as endophenotypes for discriminating between schizophrenia and depression. Copyright © 2017 Elsevier B.V. All rights reserved.

Characterization of healthy and osteoarthritic chondrocyte cell patterns on phase contrast CT images of the knee cartilage matrix

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Yang, Chien-Chun; Glaser, Christian; Reiser, Maximilian F.; Wismüller, Axel

2012-03-01

The current approach to evaluating cartilage degeneration at the knee joint requires visualization of the joint space on radiographic images where indirect cues such as joint space narrowing serve as markers for osteoarthritis. A recent novel approach to visualizing the knee cartilage matrix using phase contrast CT imaging (PCI-CT) was shown to allow direct examination of chondrocyte cell patterns and their subsequent correlation to osteoarthritis. This study aims to characterize chondrocyte cell patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage through both gray-level co-occurrence matrix (GLCM) derived texture features as well as Minkowski Functionals (MF). Thirteen GLCM and three MF texture features were extracted from 404 regions of interest (ROI) annotated on PCI images of healthy and osteoarthritic specimens of knee cartilage. These texture features were then used in a machine learning task to classify ROIs as healthy or osteoarthritic. A fuzzy k-nearest neighbor classifier was used and its performance was evaluated using the area under the ROC curve (AUC). The best classification performance was observed with the MF features 'perimeter' and 'Euler characteristic' and with GLCM correlation features (f3 and f13). With the experimental conditions used in this study, both Minkowski Functionals and GLCM achieved a high classification performance (AUC value of 0.97) in the task of distinguishing between health and osteoarthritic ROIs. These results show that such quantitative analysis of chondrocyte patterns in the knee cartilage matrix can distinguish between healthy and osteoarthritic tissue with high accuracy.

Search strategy selection in the Morris water maze indicates allocentric map formation during learning that underpins spatial memory formation.

PubMed

Rogers, Jake; Churilov, Leonid; Hannan, Anthony J; Renoir, Thibault

2017-03-01

Using a Matlab classification algorithm, we demonstrate that a highly salient distal cue array is required for significantly increased likelihoods of spatial search strategy selection during Morris water maze spatial learning. We hypothesized that increased spatial search strategy selection during spatial learning would be the key measure demonstrating the formation of an allocentric map to the escape location. Spatial memory, as indicated by quadrant preference for the area of the pool formally containing the hidden platform, was assessed as the main measure that this allocentric map had formed during spatial learning. Our C57BL/6J wild-type (WT) mice exhibit quadrant preference in the highly salient cue paradigm but not the low, corresponding with a 120% increase in the odds of a spatial search strategy selection during learning. In contrast, quadrant preference remains absent in serotonin 1A receptor (5-HT 1A R) knockout (KO) mice, who exhibit impaired search strategy selection during spatial learning. Additionally, we also aimed to assess the impact of the quality of the distal cue array on the spatial learning curves of both latency to platform and path length using mixed-effect regression models and found no significant associations or interactions. In contrast, we demonstrated that the spatial learning curve for search strategy selection was absent during training in the low saliency paradigm. Therefore, we propose that allocentric search strategy selection during spatial learning is the learning parameter in mice that robustly indicates the formation of a cognitive map for the escape goal location. These results also suggest that both latency to platform and path length spatial learning curves do not discriminate between allocentric and egocentric spatial learning and do not reliably predict spatial memory formation. We also show that spatial memory, as indicated by the absolute time in the quadrant formerly containing the hidden platform alone (without reference to the other areas of the pool), was not sensitive to cue saliency or impaired in 5-HT 1A R KO mice. Importantly, in the absence of a search strategy analysis, this suggests that to establish that the Morris water maze has worked (i.e. control mice have formed an allocentric map to the escape goal location), a measure of quadrant preference needs to be reported to establish spatial memory formation. This has implications for studies that claim hippocampal functioning is impaired using latency to platform or path length differences within the existing Morris water maze literature. Copyright © 2016 Elsevier Inc. All rights reserved.

Study of optimizing water utilization in Benanga reservoir for irrigation and fresh water purposes

NASA Astrophysics Data System (ADS)

Tamrin; Retati, E.

2018-04-01

Benanga dam was built in1978an irrigation weir but currently it was developed into a multipurpose dam. However, based on the capacity curve measurement in 2015, the capacity curve measurement has been changed to get below. The runoff rate is calculated by using NRECA method, andwater reservoir volume is calculated by using penman modification method. The cropping pattern that has been implemented by the farmer of Lempake sincein Februaryis Paddy-Paddy-Fallow While the proposed cropping pattern in Benanga reservoir started on December, that proposed is based on the service ability for both raw water demands like irrigation and fresh water and if early planting is started besides these two months the elevation of benanga reservoir will not reach the normal elevation effective storage which is the condition pattern of reservoir operation.

Perforated-Layer Implementation Of Radio-Frequency Lenses

NASA Technical Reports Server (NTRS)

Dolgin, Benjamin P.

1996-01-01

Luneberg-type radio-frequency dielectric lenses made of stacked perforated circular dielectric sheets, according to proposal. Perforation pattern designed to achieve required spatial variation of permittivity. Consists of round holes distributed across face of each sheet in "Swiss-cheese" pattern, plus straight or curved slots that break up outer parts into petals in "daisy-wheel" pattern. Holes and slots made by numerically controlled machining.

Planet Hunters: Kepler by Eye

NASA Astrophysics Data System (ADS)

Schwamb, Megan E.; Lintott, C.; Fischer, D.; Smith, A. M.; Boyajian, T. S.; Brewer, J. M.; Giguere, M. J.; Lynn, S.; Parrish, M.; Schawinski, K.; Schmitt, J.; Simpson, R.; Wang, J.

2014-01-01

Planet Hunters (http://www.planethunters.org), part of the Zooniverse's (http://www.zooniverse.org) collection of online citizen science projects, uses the World Wide Web to enlist the general public to identify transits in the pubic Kepler light curves. Planet Hunters utilizes human pattern recognition to identify planet transits that may be missed by automated detection algorithms looking for periodic events. Referred to as ‘crowdsourcing’ or ‘citizen science’, the combined assessment of many non-expert human classifiers with minimal training can often equal or best that of a trained expert and in many cases outperform the best machine-learning algorithm. Visitors to the Planet Hunters' website are presented with a randomly selected ~30-day light curve segment from one of Kepler’s ~160,000 target stars and are asked to draw boxes to mark the locations of visible transits in the web interface. 5-10 classifiers review each 30-day light curve segment. Since December 2010, more than 260,000 volunteers world wide have participated, contributing over 20 million classifications. We have demonstrated the success of a citizen science approach with the project’s more than 20 planet candidates, the discovery of PH1b, a transiting circumbinary planet in a quadruple star system, and the discovery of PH2-b, a confirmed Jupiter-sized planet in the habitable zone of a Sun-like star. I will provide an overview of Planet Hunters, highlighting several of project's most recent exoplanet and astrophysical discoveries. Acknowledgements: MES was supported in part by a NSF AAPF under award AST-1003258 and a American Philosophical Society Franklin Grant. We acknowledge support from NASA ADAP12-0172 grant to PI Fischer.

Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity

PubMed Central

Miyata, Ryota; Ota, Keisuke; Aonishi, Toru

2013-01-01

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-associative memory recalling such reversed and spread-out spike patterns. In line with Lengyel’s speculation (Lengyel et al., 2005), we firstly derive optimally designed spike-timing-dependent plasticity (STDP) rules that are matched to neural interactions formalized in terms of phase response curves (PRCs) for performing the hetero-associative memory function. By maximizing object functions formulated in terms of mutual information for evaluating memory retrieval performance, we search for STDP window functions that are optimal for retrieval of normal and doubly spread-out patterns under the constraint that the PRCs are those of CA1 pyramidal neurons. The system, which can retrieve normal and doubly spread-out patterns, can also retrieve reversed patterns with the same quality. Finally, we demonstrate that purposely designed STDP window functions qualitatively conform to typical ones found in CA1 pyramidal neurons. PMID:24204822

Multi-Probe SPM using Interference Patterns for a Parallel Nano Imaging

NASA Astrophysics Data System (ADS)

Koyama, Hirotaka; Oohira, Fumikazu; Hosogi, Maho; Hashiguchi, Gen

This paper proposes a new composition of the multi-probe using optical interference patterns for a parallel nano imaging in a large area scanning. We achieved large-scale integration with 50,000 probes fabricated with MEMS technology, and measured the optical interference patterns with CCD, which was difficult in a conventional single scanning probe. In this research, the multi-probes are made of Si3N4 by MEMS process, and, the multi-probes are joined with a Pyrex glass by an anodic bonding. We designed, fabricated, and evaluated the characteristics of the probe. In addition, we changed the probe shape to decrease the warpage of the Si3N4 probe. We used the supercritical drying to avoid stiction of the Si3N4 probe with the glass surface and fabricated 4 types of the probe shapes without stiction. We took some interference patterns by CCD and measured the position of them. We calculate the probe height using the interference displacement and compared the result with the theoretical deflection curve. As a result, these interference patterns matched the theoretical deflection curve. We found that this multi-probe chip using interference patterns is effective in measurement for a parallel nano imaging.